Overview

Dataset statistics

Number of variables369
Number of observations191652
Missing cells13864774
Missing cells (%)19.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory597.7 MiB
Average record size in memory3.2 KiB

Variable types

NUM329
CAT33
BOOL7

Warnings

EINGEFUEGT_AM has a high cardinality: 3034 distinct values High cardinality
AKT_DAT_KL has 46596 (24.3%) missing values Missing
ALTER_HH has 46596 (24.3%) missing values Missing
ALTER_KIND1 has 179886 (93.9%) missing values Missing
ALTER_KIND2 has 186552 (97.3%) missing values Missing
ALTER_KIND3 has 190377 (99.3%) missing values Missing
ALTER_KIND4 has 191416 (99.9%) missing values Missing
ALTERSKATEGORIE_FEIN has 51842 (27.1%) missing values Missing
ANZ_HAUSHALTE_AKTIV has 49927 (26.1%) missing values Missing
ANZ_HH_TITEL has 52110 (27.2%) missing values Missing
ANZ_KINDER has 46596 (24.3%) missing values Missing
ANZ_PERSONEN has 46596 (24.3%) missing values Missing
ANZ_STATISTISCHE_HAUSHALTE has 49927 (26.1%) missing values Missing
ANZ_TITEL has 46596 (24.3%) missing values Missing
ARBEIT has 50476 (26.3%) missing values Missing
BALLRAUM has 49959 (26.1%) missing values Missing
CAMEO_DEU_2015 has 50428 (26.3%) missing values Missing
CAMEO_DEUG_2015 has 50554 (26.4%) missing values Missing
CAMEO_INTL_2015 has 50554 (26.4%) missing values Missing
CJT_GESAMTTYP has 3213 (1.7%) missing values Missing
CJT_KATALOGNUTZER has 3213 (1.7%) missing values Missing
CJT_TYP_1 has 3213 (1.7%) missing values Missing
CJT_TYP_2 has 3213 (1.7%) missing values Missing
CJT_TYP_3 has 3213 (1.7%) missing values Missing
CJT_TYP_4 has 3213 (1.7%) missing values Missing
CJT_TYP_5 has 3213 (1.7%) missing values Missing
CJT_TYP_6 has 3213 (1.7%) missing values Missing
D19_BANKEN_ONLINE_QUOTE_12 has 47697 (24.9%) missing values Missing
D19_GESAMT_ONLINE_QUOTE_12 has 47697 (24.9%) missing values Missing
D19_KONSUMTYP has 47697 (24.9%) missing values Missing
D19_LETZTER_KAUF_BRANCHE has 47697 (24.9%) missing values Missing
D19_LOTTO has 47697 (24.9%) missing values Missing
D19_SOZIALES has 47697 (24.9%) missing values Missing
D19_TELKO_ONLINE_QUOTE_12 has 47697 (24.9%) missing values Missing
D19_VERSAND_ONLINE_QUOTE_12 has 47697 (24.9%) missing values Missing
D19_VERSI_ONLINE_QUOTE_12 has 47697 (24.9%) missing values Missing
DSL_FLAG has 49927 (26.1%) missing values Missing
EINGEFUEGT_AM has 49927 (26.1%) missing values Missing
EINGEZOGENAM_HH_JAHR has 46596 (24.3%) missing values Missing
EWDICHTE has 49959 (26.1%) missing values Missing
EXTSEL992 has 85283 (44.5%) missing values Missing
FIRMENDICHTE has 49927 (26.1%) missing values Missing
GEBAEUDETYP has 49927 (26.1%) missing values Missing
GEBAEUDETYP_RASTER has 49927 (26.1%) missing values Missing
GEMEINDETYP has 50476 (26.3%) missing values Missing
GFK_URLAUBERTYP has 3213 (1.7%) missing values Missing
HH_DELTA_FLAG has 53742 (28.0%) missing values Missing
HH_EINKOMMEN_SCORE has 2968 (1.5%) missing values Missing
INNENSTADT has 49959 (26.1%) missing values Missing
KBA05_ALTER1 has 55980 (29.2%) missing values Missing
KBA05_ALTER2 has 55980 (29.2%) missing values Missing
KBA05_ALTER3 has 55980 (29.2%) missing values Missing
KBA05_ALTER4 has 55980 (29.2%) missing values Missing
KBA05_ANHANG has 55980 (29.2%) missing values Missing
KBA05_ANTG1 has 55980 (29.2%) missing values Missing
KBA05_ANTG2 has 55980 (29.2%) missing values Missing
KBA05_ANTG3 has 55980 (29.2%) missing values Missing
KBA05_ANTG4 has 55980 (29.2%) missing values Missing
KBA05_AUTOQUOT has 55980 (29.2%) missing values Missing
KBA05_BAUMAX has 55980 (29.2%) missing values Missing
KBA05_CCM1 has 55980 (29.2%) missing values Missing
KBA05_CCM2 has 55980 (29.2%) missing values Missing
KBA05_CCM3 has 55980 (29.2%) missing values Missing
KBA05_CCM4 has 55980 (29.2%) missing values Missing
KBA05_DIESEL has 55980 (29.2%) missing values Missing
KBA05_FRAU has 55980 (29.2%) missing values Missing
KBA05_GBZ has 55980 (29.2%) missing values Missing
KBA05_HERST1 has 55980 (29.2%) missing values Missing
KBA05_HERST2 has 55980 (29.2%) missing values Missing
KBA05_HERST3 has 55980 (29.2%) missing values Missing
KBA05_HERST4 has 55980 (29.2%) missing values Missing
KBA05_HERST5 has 55980 (29.2%) missing values Missing
KBA05_HERSTTEMP has 49927 (26.1%) missing values Missing
KBA05_KRSAQUOT has 55980 (29.2%) missing values Missing
KBA05_KRSHERST1 has 55980 (29.2%) missing values Missing
KBA05_KRSHERST2 has 55980 (29.2%) missing values Missing
KBA05_KRSHERST3 has 55980 (29.2%) missing values Missing
KBA05_KRSKLEIN has 55980 (29.2%) missing values Missing
KBA05_KRSOBER has 55980 (29.2%) missing values Missing
KBA05_KRSVAN has 55980 (29.2%) missing values Missing
KBA05_KRSZUL has 55980 (29.2%) missing values Missing
KBA05_KW1 has 55980 (29.2%) missing values Missing
KBA05_KW2 has 55980 (29.2%) missing values Missing
KBA05_KW3 has 55980 (29.2%) missing values Missing
KBA05_MAXAH has 55980 (29.2%) missing values Missing
KBA05_MAXBJ has 55980 (29.2%) missing values Missing
KBA05_MAXHERST has 55980 (29.2%) missing values Missing
KBA05_MAXSEG has 55980 (29.2%) missing values Missing
KBA05_MAXVORB has 55980 (29.2%) missing values Missing
KBA05_MOD1 has 55980 (29.2%) missing values Missing
KBA05_MOD2 has 55980 (29.2%) missing values Missing
KBA05_MOD3 has 55980 (29.2%) missing values Missing
KBA05_MOD4 has 55980 (29.2%) missing values Missing
KBA05_MOD8 has 55980 (29.2%) missing values Missing
KBA05_MODTEMP has 49927 (26.1%) missing values Missing
KBA05_MOTOR has 55980 (29.2%) missing values Missing
KBA05_MOTRAD has 55980 (29.2%) missing values Missing
KBA05_SEG1 has 55980 (29.2%) missing values Missing
KBA05_SEG10 has 55980 (29.2%) missing values Missing
KBA05_SEG2 has 55980 (29.2%) missing values Missing
KBA05_SEG3 has 55980 (29.2%) missing values Missing
KBA05_SEG4 has 55980 (29.2%) missing values Missing
KBA05_SEG5 has 55980 (29.2%) missing values Missing
KBA05_SEG6 has 55980 (29.2%) missing values Missing
KBA05_SEG7 has 55980 (29.2%) missing values Missing
KBA05_SEG8 has 55980 (29.2%) missing values Missing
KBA05_SEG9 has 55980 (29.2%) missing values Missing
KBA05_VORB0 has 55980 (29.2%) missing values Missing
KBA05_VORB1 has 55980 (29.2%) missing values Missing
KBA05_VORB2 has 55980 (29.2%) missing values Missing
KBA05_ZUL1 has 55980 (29.2%) missing values Missing
KBA05_ZUL2 has 55980 (29.2%) missing values Missing
KBA05_ZUL3 has 55980 (29.2%) missing values Missing
KBA05_ZUL4 has 55980 (29.2%) missing values Missing
KBA13_ALTERHALTER_30 has 51281 (26.8%) missing values Missing
KBA13_ALTERHALTER_45 has 51281 (26.8%) missing values Missing
KBA13_ALTERHALTER_60 has 51281 (26.8%) missing values Missing
KBA13_ALTERHALTER_61 has 51281 (26.8%) missing values Missing
KBA13_ANTG1 has 51281 (26.8%) missing values Missing
KBA13_ANTG2 has 51281 (26.8%) missing values Missing
KBA13_ANTG3 has 51281 (26.8%) missing values Missing
KBA13_ANTG4 has 51281 (26.8%) missing values Missing
KBA13_ANZAHL_PKW has 51281 (26.8%) missing values Missing
KBA13_AUDI has 51281 (26.8%) missing values Missing
KBA13_AUTOQUOTE has 51281 (26.8%) missing values Missing
KBA13_BAUMAX has 51281 (26.8%) missing values Missing
KBA13_BJ_1999 has 51281 (26.8%) missing values Missing
KBA13_BJ_2000 has 51281 (26.8%) missing values Missing
KBA13_BJ_2004 has 51281 (26.8%) missing values Missing
KBA13_BJ_2006 has 51281 (26.8%) missing values Missing
KBA13_BJ_2008 has 51281 (26.8%) missing values Missing
KBA13_BJ_2009 has 51281 (26.8%) missing values Missing
KBA13_BMW has 51281 (26.8%) missing values Missing
KBA13_CCM_0_1400 has 51281 (26.8%) missing values Missing
KBA13_CCM_1000 has 51281 (26.8%) missing values Missing
KBA13_CCM_1200 has 51281 (26.8%) missing values Missing
KBA13_CCM_1400 has 51281 (26.8%) missing values Missing
KBA13_CCM_1401_2500 has 51281 (26.8%) missing values Missing
KBA13_CCM_1500 has 51281 (26.8%) missing values Missing
KBA13_CCM_1600 has 51281 (26.8%) missing values Missing
KBA13_CCM_1800 has 51281 (26.8%) missing values Missing
KBA13_CCM_2000 has 51281 (26.8%) missing values Missing
KBA13_CCM_2500 has 51281 (26.8%) missing values Missing
KBA13_CCM_2501 has 51281 (26.8%) missing values Missing
KBA13_CCM_3000 has 51281 (26.8%) missing values Missing
KBA13_CCM_3001 has 51281 (26.8%) missing values Missing
KBA13_FAB_ASIEN has 51281 (26.8%) missing values Missing
KBA13_FAB_SONSTIGE has 51281 (26.8%) missing values Missing
KBA13_FIAT has 51281 (26.8%) missing values Missing
KBA13_FORD has 51281 (26.8%) missing values Missing
KBA13_GBZ has 51281 (26.8%) missing values Missing
KBA13_HALTER_20 has 51281 (26.8%) missing values Missing
KBA13_HALTER_25 has 51281 (26.8%) missing values Missing
KBA13_HALTER_30 has 51281 (26.8%) missing values Missing
KBA13_HALTER_35 has 51281 (26.8%) missing values Missing
KBA13_HALTER_40 has 51281 (26.8%) missing values Missing
KBA13_HALTER_45 has 51281 (26.8%) missing values Missing
KBA13_HALTER_50 has 51281 (26.8%) missing values Missing
KBA13_HALTER_55 has 51281 (26.8%) missing values Missing
KBA13_HALTER_60 has 51281 (26.8%) missing values Missing
KBA13_HALTER_65 has 51281 (26.8%) missing values Missing
KBA13_HALTER_66 has 51281 (26.8%) missing values Missing
KBA13_HERST_ASIEN has 51281 (26.8%) missing values Missing
KBA13_HERST_AUDI_VW has 51281 (26.8%) missing values Missing
KBA13_HERST_BMW_BENZ has 51281 (26.8%) missing values Missing
KBA13_HERST_EUROPA has 51281 (26.8%) missing values Missing
KBA13_HERST_FORD_OPEL has 51281 (26.8%) missing values Missing
KBA13_HERST_SONST has 51281 (26.8%) missing values Missing
KBA13_HHZ has 51281 (26.8%) missing values Missing
KBA13_KMH_0_140 has 51281 (26.8%) missing values Missing
KBA13_KMH_110 has 51281 (26.8%) missing values Missing
KBA13_KMH_140 has 51281 (26.8%) missing values Missing
KBA13_KMH_140_210 has 51281 (26.8%) missing values Missing
KBA13_KMH_180 has 51281 (26.8%) missing values Missing
KBA13_KMH_210 has 51281 (26.8%) missing values Missing
KBA13_KMH_211 has 51281 (26.8%) missing values Missing
KBA13_KMH_250 has 51281 (26.8%) missing values Missing
KBA13_KMH_251 has 51281 (26.8%) missing values Missing
KBA13_KRSAQUOT has 51281 (26.8%) missing values Missing
KBA13_KRSHERST_AUDI_VW has 51281 (26.8%) missing values Missing
KBA13_KRSHERST_BMW_BENZ has 51281 (26.8%) missing values Missing
KBA13_KRSHERST_FORD_OPEL has 51281 (26.8%) missing values Missing
KBA13_KRSSEG_KLEIN has 51281 (26.8%) missing values Missing
KBA13_KRSSEG_OBER has 51281 (26.8%) missing values Missing
KBA13_KRSSEG_VAN has 51281 (26.8%) missing values Missing
KBA13_KRSZUL_NEU has 51281 (26.8%) missing values Missing
KBA13_KW_0_60 has 51281 (26.8%) missing values Missing
KBA13_KW_110 has 51281 (26.8%) missing values Missing
KBA13_KW_120 has 51281 (26.8%) missing values Missing
KBA13_KW_121 has 51281 (26.8%) missing values Missing
KBA13_KW_30 has 51281 (26.8%) missing values Missing
KBA13_KW_40 has 51281 (26.8%) missing values Missing
KBA13_KW_50 has 51281 (26.8%) missing values Missing
KBA13_KW_60 has 51281 (26.8%) missing values Missing
KBA13_KW_61_120 has 51281 (26.8%) missing values Missing
KBA13_KW_70 has 51281 (26.8%) missing values Missing
KBA13_KW_80 has 51281 (26.8%) missing values Missing
KBA13_KW_90 has 51281 (26.8%) missing values Missing
KBA13_MAZDA has 51281 (26.8%) missing values Missing
KBA13_MERCEDES has 51281 (26.8%) missing values Missing
KBA13_MOTOR has 51281 (26.8%) missing values Missing
KBA13_NISSAN has 51281 (26.8%) missing values Missing
KBA13_OPEL has 51281 (26.8%) missing values Missing
KBA13_PEUGEOT has 51281 (26.8%) missing values Missing
KBA13_RENAULT has 51281 (26.8%) missing values Missing
KBA13_SEG_GELAENDEWAGEN has 51281 (26.8%) missing values Missing
KBA13_SEG_GROSSRAUMVANS has 51281 (26.8%) missing values Missing
KBA13_SEG_KLEINST has 51281 (26.8%) missing values Missing
KBA13_SEG_KLEINWAGEN has 51281 (26.8%) missing values Missing
KBA13_SEG_KOMPAKTKLASSE has 51281 (26.8%) missing values Missing
KBA13_SEG_MINIVANS has 51281 (26.8%) missing values Missing
KBA13_SEG_MINIWAGEN has 51281 (26.8%) missing values Missing
KBA13_SEG_MITTELKLASSE has 51281 (26.8%) missing values Missing
KBA13_SEG_OBEREMITTELKLASSE has 51281 (26.8%) missing values Missing
KBA13_SEG_OBERKLASSE has 51281 (26.8%) missing values Missing
KBA13_SEG_SONSTIGE has 51281 (26.8%) missing values Missing
KBA13_SEG_SPORTWAGEN has 51281 (26.8%) missing values Missing
KBA13_SEG_UTILITIES has 51281 (26.8%) missing values Missing
KBA13_SEG_VAN has 51281 (26.8%) missing values Missing
KBA13_SEG_WOHNMOBILE has 51281 (26.8%) missing values Missing
KBA13_SITZE_4 has 51281 (26.8%) missing values Missing
KBA13_SITZE_5 has 51281 (26.8%) missing values Missing
KBA13_SITZE_6 has 51281 (26.8%) missing values Missing
KBA13_TOYOTA has 51281 (26.8%) missing values Missing
KBA13_VORB_0 has 51281 (26.8%) missing values Missing
KBA13_VORB_1 has 51281 (26.8%) missing values Missing
KBA13_VORB_1_2 has 51281 (26.8%) missing values Missing
KBA13_VORB_2 has 51281 (26.8%) missing values Missing
KBA13_VORB_3 has 51281 (26.8%) missing values Missing
KBA13_VW has 51281 (26.8%) missing values Missing
KK_KUNDENTYP has 111937 (58.4%) missing values Missing
KKK has 54260 (28.3%) missing values Missing
KONSUMNAEHE has 46651 (24.3%) missing values Missing
KONSUMZELLE has 49927 (26.1%) missing values Missing
LP_FAMILIE_FEIN has 3213 (1.7%) missing values Missing
LP_FAMILIE_GROB has 3213 (1.7%) missing values Missing
LP_LEBENSPHASE_FEIN has 3213 (1.7%) missing values Missing
LP_LEBENSPHASE_GROB has 3213 (1.7%) missing values Missing
LP_STATUS_FEIN has 3213 (1.7%) missing values Missing
LP_STATUS_GROB has 3213 (1.7%) missing values Missing
MIN_GEBAEUDEJAHR has 49927 (26.1%) missing values Missing
MOBI_RASTER has 49927 (26.1%) missing values Missing
MOBI_REGIO has 55980 (29.2%) missing values Missing
ONLINE_AFFINITAET has 3213 (1.7%) missing values Missing
ORTSGR_KLS9 has 50476 (26.3%) missing values Missing
OST_WEST_KZ has 49927 (26.1%) missing values Missing
PLZ8_ANTG1 has 52764 (27.5%) missing values Missing
PLZ8_ANTG2 has 52764 (27.5%) missing values Missing
PLZ8_ANTG3 has 52764 (27.5%) missing values Missing
PLZ8_ANTG4 has 52764 (27.5%) missing values Missing
PLZ8_BAUMAX has 52764 (27.5%) missing values Missing
PLZ8_GBZ has 52764 (27.5%) missing values Missing
PLZ8_HHZ has 52764 (27.5%) missing values Missing
REGIOTYP has 54260 (28.3%) missing values Missing
RELAT_AB has 50476 (26.3%) missing values Missing
RETOURTYP_BK_S has 3213 (1.7%) missing values Missing
RT_KEIN_ANREIZ has 3213 (1.7%) missing values Missing
RT_SCHNAEPPCHEN has 3213 (1.7%) missing values Missing
RT_UEBERGROESSE has 44192 (23.1%) missing values Missing
SOHO_KZ has 46596 (24.3%) missing values Missing
STRUKTURTYP has 50476 (26.3%) missing values Missing
TITEL_KZ has 46596 (24.3%) missing values Missing
UMFELD_ALT has 50448 (26.3%) missing values Missing
UMFELD_JUNG has 50448 (26.3%) missing values Missing
UNGLEICHENN_FLAG has 46596 (24.3%) missing values Missing
VERDICHTUNGSRAUM has 50476 (26.3%) missing values Missing
VHA has 46596 (24.3%) missing values Missing
VHN has 54260 (28.3%) missing values Missing
VK_DHT4A has 47871 (25.0%) missing values Missing
VK_DISTANZ has 47871 (25.0%) missing values Missing
VK_ZG11 has 47871 (25.0%) missing values Missing
W_KEIT_KIND_HH has 53742 (28.0%) missing values Missing
WOHNDAUER_2008 has 46596 (24.3%) missing values Missing
WOHNLAGE has 49927 (26.1%) missing values Missing
ANZ_HH_TITEL is highly skewed (γ1 = 21.21510331) Skewed
LNR has unique values Unique
AGER_TYP has 4631 (2.4%) zeros Zeros
ALTER_HH has 22151 (11.6%) zeros Zeros
ALTERSKATEGORIE_FEIN has 11019 (5.7%) zeros Zeros
ANZ_HAUSHALTE_AKTIV has 2450 (1.3%) zeros Zeros
ANZ_HH_TITEL has 133454 (69.6%) zeros Zeros
ANZ_KINDER has 132284 (69.0%) zeros Zeros
ANZ_PERSONEN has 7146 (3.7%) zeros Zeros
ANZ_TITEL has 142316 (74.3%) zeros Zeros
D19_BANKEN_ANZ_12 has 180150 (94.0%) zeros Zeros
D19_BANKEN_ANZ_24 has 173701 (90.6%) zeros Zeros
D19_BANKEN_DIREKT has 166726 (87.0%) zeros Zeros
D19_BANKEN_GROSS has 175064 (91.3%) zeros Zeros
D19_BANKEN_LOKAL has 187347 (97.8%) zeros Zeros
D19_BANKEN_ONLINE_QUOTE_12 has 137161 (71.6%) zeros Zeros
D19_BANKEN_REST has 176243 (92.0%) zeros Zeros
D19_BEKLEIDUNG_GEH has 154242 (80.5%) zeros Zeros
D19_BEKLEIDUNG_REST has 137848 (71.9%) zeros Zeros
D19_BILDUNG has 155747 (81.3%) zeros Zeros
D19_BIO_OEKO has 174542 (91.1%) zeros Zeros
D19_BUCH_CD has 102937 (53.7%) zeros Zeros
D19_DIGIT_SERV has 183539 (95.8%) zeros Zeros
D19_DROGERIEARTIKEL has 160837 (83.9%) zeros Zeros
D19_ENERGIE has 172916 (90.2%) zeros Zeros
D19_FREIZEIT has 166363 (86.8%) zeros Zeros
D19_GARTEN has 179969 (93.9%) zeros Zeros
D19_GESAMT_ANZ_12 has 111999 (58.4%) zeros Zeros
D19_GESAMT_ANZ_24 has 91722 (47.9%) zeros Zeros
D19_GESAMT_ONLINE_QUOTE_12 has 86879 (45.3%) zeros Zeros
D19_HANDWERK has 143537 (74.9%) zeros Zeros
D19_HAUS_DEKO has 132811 (69.3%) zeros Zeros
D19_KINDERARTIKEL has 153651 (80.2%) zeros Zeros
D19_KOSMETIK has 139367 (72.7%) zeros Zeros
D19_LEBENSMITTEL has 170971 (89.2%) zeros Zeros
D19_LOTTO has 88281 (46.1%) zeros Zeros
D19_NAHRUNGSERGAENZUNG has 174094 (90.8%) zeros Zeros
D19_RATGEBER has 161270 (84.1%) zeros Zeros
D19_REISEN has 134825 (70.3%) zeros Zeros
D19_SAMMELARTIKEL has 145113 (75.7%) zeros Zeros
D19_SCHUHE has 163720 (85.4%) zeros Zeros
D19_SONSTIGE has 76573 (40.0%) zeros Zeros
D19_SOZIALES has 22750 (11.9%) zeros Zeros
D19_TECHNIK has 117416 (61.3%) zeros Zeros
D19_TELKO_ANZ_12 has 184467 (96.3%) zeros Zeros
D19_TELKO_ANZ_24 has 178411 (93.1%) zeros Zeros
D19_TELKO_MOBILE has 159544 (83.2%) zeros Zeros
D19_TELKO_REST has 168650 (88.0%) zeros Zeros
D19_TIERARTIKEL has 183788 (95.9%) zeros Zeros
D19_VERSAND_ANZ_12 has 122306 (63.8%) zeros Zeros
D19_VERSAND_ANZ_24 has 102484 (53.5%) zeros Zeros
D19_VERSAND_ONLINE_QUOTE_12 has 92458 (48.2%) zeros Zeros
D19_VERSAND_REST has 161199 (84.1%) zeros Zeros
D19_VERSI_ANZ_12 has 177236 (92.5%) zeros Zeros
D19_VERSI_ANZ_24 has 168832 (88.1%) zeros Zeros
D19_VERSICHERUNGEN has 144720 (75.5%) zeros Zeros
D19_VOLLSORTIMENT has 108259 (56.5%) zeros Zeros
D19_WEIN_FEINKOST has 166431 (86.8%) zeros Zeros
GEBURTSJAHR has 93024 (48.5%) zeros Zeros
KBA05_ALTER1 has 22932 (12.0%) zeros Zeros
KBA05_ALTER4 has 2435 (1.3%) zeros Zeros
KBA05_ANHANG has 36170 (18.9%) zeros Zeros
KBA05_ANTG1 has 22465 (11.7%) zeros Zeros
KBA05_ANTG2 has 43729 (22.8%) zeros Zeros
KBA05_BAUMAX has 53555 (27.9%) zeros Zeros
KBA05_CCM4 has 32427 (16.9%) zeros Zeros
KBA05_DIESEL has 5076 (2.6%) zeros Zeros
KBA05_HERST1 has 5354 (2.8%) zeros Zeros
KBA05_HERST3 has 1918 (1.0%) zeros Zeros
KBA05_HERST4 has 3323 (1.7%) zeros Zeros
KBA05_HERST5 has 6536 (3.4%) zeros Zeros
KBA05_KW3 has 20709 (10.8%) zeros Zeros
KBA05_MOD1 has 32586 (17.0%) zeros Zeros
KBA05_MOD4 has 5107 (2.7%) zeros Zeros
KBA05_MOD8 has 26798 (14.0%) zeros Zeros
KBA05_MOTRAD has 26539 (13.8%) zeros Zeros
KBA05_SEG1 has 36867 (19.2%) zeros Zeros
KBA05_SEG10 has 9635 (5.0%) zeros Zeros
KBA05_SEG5 has 18467 (9.6%) zeros Zeros
KBA05_SEG7 has 53730 (28.0%) zeros Zeros
KBA05_SEG8 has 54785 (28.6%) zeros Zeros
KBA05_SEG9 has 34324 (17.9%) zeros Zeros
KBA05_VORB2 has 11641 (6.1%) zeros Zeros
KBA05_ZUL3 has 5137 (2.7%) zeros Zeros
KBA05_ZUL4 has 8776 (4.6%) zeros Zeros
KBA13_BJ_2008 has 19625 (10.2%) zeros Zeros
KBA13_BJ_2009 has 16351 (8.5%) zeros Zeros
KBA13_CCM_0_1400 has 28511 (14.9%) zeros Zeros
KBA13_CCM_1000 has 19982 (10.4%) zeros Zeros
KBA13_CCM_1200 has 29378 (15.3%) zeros Zeros
KBA13_CCM_1800 has 24878 (13.0%) zeros Zeros
KBA13_CCM_2500 has 15780 (8.2%) zeros Zeros
KBA13_CCM_2501 has 14392 (7.5%) zeros Zeros
KBA13_CCM_3000 has 9117 (4.8%) zeros Zeros
KBA13_KMH_0_140 has 21541 (11.2%) zeros Zeros
KBA13_KMH_211 has 20007 (10.4%) zeros Zeros
KBA13_KMH_250 has 20125 (10.5%) zeros Zeros
KBA13_KW_110 has 19148 (10.0%) zeros Zeros
KBA13_KW_120 has 17157 (9.0%) zeros Zeros
KBA13_KW_121 has 15218 (7.9%) zeros Zeros
KBA13_KW_40 has 19498 (10.2%) zeros Zeros
KBA13_KW_50 has 29204 (15.2%) zeros Zeros
KBA13_KW_60 has 24799 (12.9%) zeros Zeros
KBA13_KW_70 has 27083 (14.1%) zeros Zeros
KBA13_KW_80 has 23396 (12.2%) zeros Zeros
KBA13_KW_90 has 23538 (12.3%) zeros Zeros
KBA13_SEG_OBERKLASSE has 14998 (7.8%) zeros Zeros
KBA13_SEG_SPORTWAGEN has 14430 (7.5%) zeros Zeros
KBA13_SEG_WOHNMOBILE has 15839 (8.3%) zeros Zeros
KBA13_VORB_3 has 31766 (16.6%) zeros Zeros
KKK has 5804 (3.0%) zeros Zeros
LP_FAMILIE_FEIN has 47369 (24.7%) zeros Zeros
LP_FAMILIE_GROB has 47369 (24.7%) zeros Zeros
LP_LEBENSPHASE_FEIN has 47840 (25.0%) zeros Zeros
LP_LEBENSPHASE_GROB has 47728 (24.9%) zeros Zeros
ONLINE_AFFINITAET has 4110 (2.1%) zeros Zeros
PRAEGENDE_JUGENDJAHRE has 48487 (25.3%) zeros Zeros
REGIOTYP has 5804 (3.0%) zeros Zeros
SHOPPER_TYP has 30054 (15.7%) zeros Zeros
TITEL_KZ has 142744 (74.5%) zeros Zeros
VERDICHTUNGSRAUM has 65984 (34.4%) zeros Zeros
VHA has 74250 (38.7%) zeros Zeros
VHN has 5804 (3.0%) zeros Zeros
W_KEIT_KIND_HH has 3195 (1.7%) zeros Zeros

Reproduction

Analysis started2020-11-30 14:54:53.307038
Analysis finished2020-11-30 14:55:10.172612
Duration16.87 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

LNR
Real number (ℝ≥0)

UNIQUE

Distinct191652
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95826.5
Minimum1
Maximum191652
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:10.324970image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9583.55
Q147913.75
median95826.5
Q3143739.25
95-th percentile182069.45
Maximum191652
Range191651
Interquartile range (IQR)95825.5

Descriptive statistics

Standard deviation55325.31123
Coefficient of variation (CV)0.5773487629
Kurtosis-1.2
Mean95826.5
Median Absolute Deviation (MAD)47913
Skewness-4.929942205e-19
Sum1.836534038e+10
Variance3060890063
MonotocityNot monotonic
2020-11-30T23:55:10.454036image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
1611241< 0.1%
 
1467971< 0.1%
 
1447481< 0.1%
 
1345071< 0.1%
 
1324581< 0.1%
 
1386011< 0.1%
 
1365521< 0.1%
 
1590791< 0.1%
 
1570301< 0.1%
 
1631731< 0.1%
 
1508831< 0.1%
 
382001< 0.1%
 
1488341< 0.1%
 
1549771< 0.1%
 
1529281< 0.1%
 
443511< 0.1%
 
423021< 0.1%
 
484451< 0.1%
 
463961< 0.1%
 
361551< 0.1%
 
341061< 0.1%
 
1406541< 0.1%
 
1427031< 0.1%
 
1857121< 0.1%
 
Other values (191627)191627> 99.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
61< 0.1%
 
71< 0.1%
 
81< 0.1%
 
91< 0.1%
 
101< 0.1%
 
ValueCountFrequency (%) 
1916521< 0.1%
 
1916511< 0.1%
 
1916501< 0.1%
 
1916491< 0.1%
 
1916481< 0.1%
 
1916471< 0.1%
 
1916461< 0.1%
 
1916451< 0.1%
 
1916441< 0.1%
 
1916431< 0.1%
 

AGER_TYP
Real number (ℝ)

ZEROS

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3443585248
Minimum-1
Maximum3
Zeros4631
Zeros (%)2.4%
Memory size1.5 MiB
2020-11-30T23:55:10.568749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median0
Q32
95-th percentile2
Maximum3
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.391672212
Coefficient of variation (CV)4.04134677
Kurtosis-1.492534609
Mean0.3443585248
Median Absolute Deviation (MAD)1
Skewness0.3053870479
Sum65997
Variance1.936751545
MonotocityNot monotonic
2020-11-30T23:55:10.648882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
-19210748.1%
 
24587423.9%
 
14038221.1%
 
386584.5%
 
046312.4%
 
ValueCountFrequency (%) 
-19210748.1%
 
046312.4%
 
14038221.1%
 
24587423.9%
 
386584.5%
 
ValueCountFrequency (%) 
386584.5%
 
24587423.9%
 
14038221.1%
 
046312.4%
 
-19210748.1%
 

AKT_DAT_KL
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean1.747525094
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:10.736269image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile7
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.966333812
Coefficient of variation (CV)1.12521063
Kurtosis6.537006582
Mean1.747525094
Median Absolute Deviation (MAD)0
Skewness2.767734543
Sum253489
Variance3.86646866
MonotocityNot monotonic
2020-11-30T23:55:10.820282image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
111953562.4%
 
262143.2%
 
959813.1%
 
540962.1%
 
325161.3%
 
423111.2%
 
716490.9%
 
615750.8%
 
811790.6%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
111953562.4%
 
262143.2%
 
325161.3%
 
423111.2%
 
540962.1%
 
615750.8%
 
716490.9%
 
811790.6%
 
959813.1%
 
ValueCountFrequency (%) 
959813.1%
 
811790.6%
 
716490.9%
 
615750.8%
 
540962.1%
 
423111.2%
 
325161.3%
 
262143.2%
 
111953562.4%
 

ALTER_HH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct21
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean11.35200888
Minimum0
Maximum21
Zeros22151
Zeros (%)11.6%
Memory size1.5 MiB
2020-11-30T23:55:10.921473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median11
Q316
95-th percentile21
Maximum21
Range21
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.275026252
Coefficient of variation (CV)0.5527679126
Kurtosis-0.642090923
Mean11.35200888
Median Absolute Deviation (MAD)4
Skewness-0.406629953
Sum1646677
Variance39.37595446
MonotocityNot monotonic
2020-11-30T23:55:11.009791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
02215111.6%
 
10144887.6%
 
9129766.8%
 
1190094.7%
 
2185034.4%
 
881114.2%
 
1680114.2%
 
1277794.1%
 
1577374.0%
 
1773323.8%
 
2065543.4%
 
1864503.4%
 
1461923.2%
 
1361643.2%
 
1961363.2%
 
753072.8%
 
618481.0%
 
52280.1%
 
452< 0.1%
 
315< 0.1%
 
213< 0.1%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
02215111.6%
 
213< 0.1%
 
315< 0.1%
 
452< 0.1%
 
52280.1%
 
618481.0%
 
753072.8%
 
881114.2%
 
9129766.8%
 
10144887.6%
 
ValueCountFrequency (%) 
2185034.4%
 
2065543.4%
 
1961363.2%
 
1864503.4%
 
1773323.8%
 
1680114.2%
 
1577374.0%
 
1461923.2%
 
1361643.2%
 
1277794.1%
 

ALTER_KIND1
Real number (ℝ≥0)

MISSING

Distinct17
Distinct (%)0.1%
Missing179886
Missing (%)93.9%
Infinite0
Infinite (%)0.0%
Mean12.3372429
Minimum2
Maximum18
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:11.094783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q19
median13
Q316
95-th percentile18
Maximum18
Range16
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.006049613
Coefficient of variation (CV)0.3247119024
Kurtosis-0.9258573891
Mean12.3372429
Median Absolute Deviation (MAD)3
Skewness-0.3197443551
Sum145160
Variance16.0484335
MonotocityNot monotonic
2020-11-30T23:55:11.192716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
1811580.6%
 
1710760.6%
 
1510300.5%
 
1610270.5%
 
149490.5%
 
138820.5%
 
118130.4%
 
127910.4%
 
107790.4%
 
87660.4%
 
97630.4%
 
77230.4%
 
65480.3%
 
51790.1%
 
31300.1%
 
41160.1%
 
236< 0.1%
 
(Missing)17988693.9%
 
ValueCountFrequency (%) 
236< 0.1%
 
31300.1%
 
41160.1%
 
51790.1%
 
65480.3%
 
77230.4%
 
87660.4%
 
97630.4%
 
107790.4%
 
118130.4%
 
ValueCountFrequency (%) 
1811580.6%
 
1710760.6%
 
1610270.5%
 
1510300.5%
 
149490.5%
 
138820.5%
 
127910.4%
 
118130.4%
 
107790.4%
 
97630.4%
 

ALTER_KIND2
Real number (ℝ≥0)

MISSING

Distinct17
Distinct (%)0.3%
Missing186552
Missing (%)97.3%
Infinite0
Infinite (%)0.0%
Mean13.67235294
Minimum2
Maximum18
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:11.288791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8
Q111
median14
Q316
95-th percentile18
Maximum18
Range16
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.243334673
Coefficient of variation (CV)0.237218472
Kurtosis-0.5547774012
Mean13.67235294
Median Absolute Deviation (MAD)3
Skewness-0.5021796386
Sum69729
Variance10.5192198
MonotocityNot monotonic
2020-11-30T23:55:11.378203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
186460.3%
 
165820.3%
 
175820.3%
 
155220.3%
 
135010.3%
 
145000.3%
 
124420.2%
 
113470.2%
 
103450.2%
 
92630.1%
 
81740.1%
 
7990.1%
 
662< 0.1%
 
523< 0.1%
 
47< 0.1%
 
34< 0.1%
 
21< 0.1%
 
(Missing)18655297.3%
 
ValueCountFrequency (%) 
21< 0.1%
 
34< 0.1%
 
47< 0.1%
 
523< 0.1%
 
662< 0.1%
 
7990.1%
 
81740.1%
 
92630.1%
 
103450.2%
 
113470.2%
 
ValueCountFrequency (%) 
186460.3%
 
175820.3%
 
165820.3%
 
155220.3%
 
145000.3%
 
135010.3%
 
124420.2%
 
113470.2%
 
103450.2%
 
92630.1%
 

ALTER_KIND3
Real number (ℝ≥0)

MISSING

Distinct14
Distinct (%)1.1%
Missing190377
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean14.64705882
Minimum5
Maximum18
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:11.472720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10
Q113
median15
Q317
95-th percentile18
Maximum18
Range13
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.753786671
Coefficient of variation (CV)0.1880095317
Kurtosis0.0957002455
Mean14.64705882
Median Absolute Deviation (MAD)2
Skewness-0.7774120716
Sum18675
Variance7.583341029
MonotocityNot monotonic
2020-11-30T23:55:11.571741image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
182090.1%
 
171860.1%
 
161790.1%
 
151650.1%
 
141350.1%
 
131350.1%
 
1285< 0.1%
 
1168< 0.1%
 
1050< 0.1%
 
926< 0.1%
 
816< 0.1%
 
713< 0.1%
 
66< 0.1%
 
52< 0.1%
 
(Missing)19037799.3%
 
ValueCountFrequency (%) 
52< 0.1%
 
66< 0.1%
 
713< 0.1%
 
816< 0.1%
 
926< 0.1%
 
1050< 0.1%
 
1168< 0.1%
 
1285< 0.1%
 
131350.1%
 
141350.1%
 
ValueCountFrequency (%) 
182090.1%
 
171860.1%
 
161790.1%
 
151650.1%
 
141350.1%
 
131350.1%
 
1285< 0.1%
 
1168< 0.1%
 
1050< 0.1%
 
926< 0.1%
 

ALTER_KIND4
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)4.2%
Missing191416
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean15.37711864
Minimum8
Maximum18
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:11.663531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile11.75
Q114
median16
Q317
95-th percentile18
Maximum18
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.307652801
Coefficient of variation (CV)0.1500705597
Kurtosis0.02425654448
Mean15.37711864
Median Absolute Deviation (MAD)2
Skewness-0.7401942184
Sum3629
Variance5.32526145
MonotocityNot monotonic
2020-11-30T23:55:11.750429image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1853< 0.1%
 
1746< 0.1%
 
1534< 0.1%
 
1326< 0.1%
 
1425< 0.1%
 
1624< 0.1%
 
1216< 0.1%
 
115< 0.1%
 
104< 0.1%
 
83< 0.1%
 
(Missing)19141699.9%
 
ValueCountFrequency (%) 
83< 0.1%
 
104< 0.1%
 
115< 0.1%
 
1216< 0.1%
 
1326< 0.1%
 
1425< 0.1%
 
1534< 0.1%
 
1624< 0.1%
 
1746< 0.1%
 
1853< 0.1%
 
ValueCountFrequency (%) 
1853< 0.1%
 
1746< 0.1%
 
1624< 0.1%
 
1534< 0.1%
 
1425< 0.1%
 
1326< 0.1%
 
1216< 0.1%
 
115< 0.1%
 
104< 0.1%
 
83< 0.1%
 

ALTERSKATEGORIE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct25
Distinct (%)< 0.1%
Missing51842
Missing (%)27.1%
Infinite0
Infinite (%)0.0%
Mean10.33157857
Minimum0
Maximum25
Zeros11019
Zeros (%)5.7%
Memory size1.5 MiB
2020-11-30T23:55:11.837823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median10
Q313
95-th percentile16
Maximum25
Range25
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.134827833
Coefficient of variation (CV)0.4002125914
Kurtosis1.204872188
Mean10.33157857
Median Absolute Deviation (MAD)2
Skewness-0.7083756147
Sum1444458
Variance17.09680121
MonotocityNot monotonic
2020-11-30T23:55:11.944260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%) 
102008810.5%
 
91971310.3%
 
11135087.0%
 
12129566.8%
 
8117766.1%
 
13116296.1%
 
0110195.7%
 
14108175.6%
 
1581164.2%
 
771853.7%
 
1644772.3%
 
1724781.3%
 
623751.2%
 
1815100.8%
 
197740.4%
 
204540.2%
 
52920.2%
 
212210.1%
 
241320.1%
 
251020.1%
 
2271< 0.1%
 
469< 0.1%
 
2324< 0.1%
 
312< 0.1%
 
212< 0.1%
 
(Missing)5184227.1%
 
ValueCountFrequency (%) 
0110195.7%
 
212< 0.1%
 
312< 0.1%
 
469< 0.1%
 
52920.2%
 
623751.2%
 
771853.7%
 
8117766.1%
 
91971310.3%
 
102008810.5%
 
ValueCountFrequency (%) 
251020.1%
 
241320.1%
 
2324< 0.1%
 
2271< 0.1%
 
212210.1%
 
204540.2%
 
197740.4%
 
1815100.8%
 
1724781.3%
 
1644772.3%
 

ANZ_HAUSHALTE_AKTIV
Real number (ℝ≥0)

MISSING
ZEROS

Distinct216
Distinct (%)0.2%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean4.965863468
Minimum0
Maximum523
Zeros2450
Zeros (%)1.3%
Memory size1.5 MiB
2020-11-30T23:55:12.056168image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q34
95-th percentile18
Maximum523
Range523
Interquartile range (IQR)3

Descriptive statistics

Standard deviation14.309694
Coefficient of variation (CV)2.881612452
Kurtosis210.7926573
Mean4.965863468
Median Absolute Deviation (MAD)0
Skewness12.06098307
Sum703787
Variance204.7673425
MonotocityNot monotonic
2020-11-30T23:55:12.181330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
17273037.9%
 
22226911.6%
 
377744.1%
 
445972.4%
 
536371.9%
 
634061.8%
 
731391.6%
 
828191.5%
 
024501.3%
 
924211.3%
 
1019631.0%
 
1116490.9%
 
1214030.7%
 
1311980.6%
 
149900.5%
 
158360.4%
 
166620.3%
 
175890.3%
 
185360.3%
 
194520.2%
 
204020.2%
 
213470.2%
 
223210.2%
 
232850.1%
 
242780.1%
 
Other values (191)45722.4%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
024501.3%
 
17273037.9%
 
22226911.6%
 
377744.1%
 
445972.4%
 
536371.9%
 
634061.8%
 
731391.6%
 
828191.5%
 
924211.3%
 
ValueCountFrequency (%) 
5231< 0.1%
 
3951< 0.1%
 
3795< 0.1%
 
3671< 0.1%
 
3662< 0.1%
 
3481< 0.1%
 
34410< 0.1%
 
3311< 0.1%
 
3218< 0.1%
 
3113< 0.1%
 

ANZ_HH_TITEL
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct20
Distinct (%)< 0.1%
Missing52110
Missing (%)27.2%
Infinite0
Infinite (%)0.0%
Mean0.06741339525
Minimum0
Maximum23
Zeros133454
Zeros (%)69.6%
Memory size1.5 MiB
2020-11-30T23:55:12.285165image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum23
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5455761376
Coefficient of variation (CV)8.092993025
Kurtosis604.3403899
Mean0.06741339525
Median Absolute Deviation (MAD)0
Skewness21.21510331
Sum9407
Variance0.2976533219
MonotocityNot monotonic
2020-11-30T23:55:12.379323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%) 
013345469.6%
 
151862.7%
 
24590.2%
 
31120.1%
 
463< 0.1%
 
652< 0.1%
 
1339< 0.1%
 
732< 0.1%
 
826< 0.1%
 
525< 0.1%
 
917< 0.1%
 
1715< 0.1%
 
1112< 0.1%
 
1412< 0.1%
 
2010< 0.1%
 
108< 0.1%
 
236< 0.1%
 
155< 0.1%
 
185< 0.1%
 
124< 0.1%
 
(Missing)5211027.2%
 
ValueCountFrequency (%) 
013345469.6%
 
151862.7%
 
24590.2%
 
31120.1%
 
463< 0.1%
 
525< 0.1%
 
652< 0.1%
 
732< 0.1%
 
826< 0.1%
 
917< 0.1%
 
ValueCountFrequency (%) 
236< 0.1%
 
2010< 0.1%
 
185< 0.1%
 
1715< 0.1%
 
155< 0.1%
 
1412< 0.1%
 
1339< 0.1%
 
124< 0.1%
 
1112< 0.1%
 
108< 0.1%
 

ANZ_KINDER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct9
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean0.1364024928
Minimum0
Maximum8
Zeros132284
Zeros (%)69.0%
Memory size1.5 MiB
2020-11-30T23:55:12.468063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4932493184
Coefficient of variation (CV)3.616131261
Kurtosis21.52904533
Mean0.1364024928
Median Absolute Deviation (MAD)0
Skewness4.316314013
Sum19786
Variance0.2432948901
MonotocityNot monotonic
2020-11-30T23:55:12.554021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
013228469.0%
 
174433.9%
 
239672.1%
 
311040.6%
 
42040.1%
 
546< 0.1%
 
66< 0.1%
 
71< 0.1%
 
81< 0.1%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
013228469.0%
 
174433.9%
 
239672.1%
 
311040.6%
 
42040.1%
 
546< 0.1%
 
66< 0.1%
 
71< 0.1%
 
81< 0.1%
 
ValueCountFrequency (%) 
81< 0.1%
 
71< 0.1%
 
66< 0.1%
 
546< 0.1%
 
42040.1%
 
311040.6%
 
239672.1%
 
174433.9%
 
013228469.0%
 

ANZ_PERSONEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct18
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean2.267827598
Minimum0
Maximum21
Zeros7146
Zeros (%)3.7%
Memory size1.5 MiB
2020-11-30T23:55:12.650043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum21
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.390620148
Coefficient of variation (CV)0.6131948256
Kurtosis1.819434865
Mean2.267827598
Median Absolute Deviation (MAD)1
Skewness0.9467205475
Sum328962
Variance1.933824396
MonotocityNot monotonic
2020-11-30T23:55:12.734329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%) 
24378022.8%
 
14092921.4%
 
32723114.2%
 
4161018.4%
 
071463.7%
 
564823.4%
 
623321.2%
 
77160.4%
 
82220.1%
 
965< 0.1%
 
1022< 0.1%
 
1112< 0.1%
 
129< 0.1%
 
143< 0.1%
 
132< 0.1%
 
212< 0.1%
 
161< 0.1%
 
151< 0.1%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
071463.7%
 
14092921.4%
 
24378022.8%
 
32723114.2%
 
4161018.4%
 
564823.4%
 
623321.2%
 
77160.4%
 
82220.1%
 
965< 0.1%
 
ValueCountFrequency (%) 
212< 0.1%
 
161< 0.1%
 
151< 0.1%
 
143< 0.1%
 
132< 0.1%
 
129< 0.1%
 
1112< 0.1%
 
1022< 0.1%
 
965< 0.1%
 
82220.1%
 

ANZ_STATISTISCHE_HAUSHALTE
Real number (ℝ≥0)

MISSING

Distinct214
Distinct (%)0.2%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean4.701287705
Minimum0
Maximum375
Zeros1161
Zeros (%)0.6%
Memory size1.5 MiB
2020-11-30T23:55:12.840590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q33
95-th percentile16
Maximum375
Range375
Interquartile range (IQR)2

Descriptive statistics

Standard deviation14.18408078
Coefficient of variation (CV)3.017062913
Kurtosis224.629693
Mean4.701287705
Median Absolute Deviation (MAD)0
Skewness12.67959573
Sum666290
Variance201.1881475
MonotocityNot monotonic
2020-11-30T23:55:12.961005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
17755140.5%
 
22096110.9%
 
373253.8%
 
444522.3%
 
538122.0%
 
635571.9%
 
731271.6%
 
827821.5%
 
922751.2%
 
1018851.0%
 
1114910.8%
 
1212330.6%
 
011610.6%
 
1310380.5%
 
148400.4%
 
157170.4%
 
165760.3%
 
175090.3%
 
184100.2%
 
194000.2%
 
203420.2%
 
213310.2%
 
222730.1%
 
232490.1%
 
252260.1%
 
Other values (189)42022.2%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
011610.6%
 
17755140.5%
 
22096110.9%
 
373253.8%
 
444522.3%
 
538122.0%
 
635571.9%
 
731271.6%
 
827821.5%
 
922751.2%
 
ValueCountFrequency (%) 
3755< 0.1%
 
3711< 0.1%
 
3651< 0.1%
 
35410< 0.1%
 
33919< 0.1%
 
32211< 0.1%
 
3171< 0.1%
 
3142< 0.1%
 
3091< 0.1%
 
3045< 0.1%
 

ANZ_TITEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean0.02039212442
Minimum0
Maximum5
Zeros142316
Zeros (%)74.3%
Memory size1.5 MiB
2020-11-30T23:55:13.062315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1522340634
Coefficient of variation (CV)7.46533614
Kurtosis81.96084768
Mean0.02039212442
Median Absolute Deviation (MAD)0
Skewness8.306930432
Sum2958
Variance0.02317521006
MonotocityNot monotonic
2020-11-30T23:55:13.146139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
014231674.3%
 
125331.3%
 
21980.1%
 
38< 0.1%
 
51< 0.1%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
014231674.3%
 
125331.3%
 
21980.1%
 
38< 0.1%
 
51< 0.1%
 
ValueCountFrequency (%) 
51< 0.1%
 
38< 0.1%
 
21980.1%
 
125331.3%
 
014231674.3%
 

ARBEIT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing50476
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean2.824849833
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:13.228209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.012414744
Coefficient of variation (CV)0.3583959518
Kurtosis-0.5611519002
Mean2.824849833
Median Absolute Deviation (MAD)1
Skewness-0.2080778722
Sum398801
Variance1.024983615
MonotocityNot monotonic
2020-11-30T23:55:13.308245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35090526.6%
 
43759519.6%
 
23333417.4%
 
1169418.8%
 
523781.2%
 
923< 0.1%
 
(Missing)5047626.3%
 
ValueCountFrequency (%) 
1169418.8%
 
23333417.4%
 
35090526.6%
 
43759519.6%
 
523781.2%
 
923< 0.1%
 
ValueCountFrequency (%) 
923< 0.1%
 
523781.2%
 
43759519.6%
 
35090526.6%
 
23333417.4%
 
1169418.8%
 

BALLRAUM
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing49959
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean4.301758026
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:13.393533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.114613777
Coefficient of variation (CV)0.4915696708
Kurtosis-1.425908566
Mean4.301758026
Median Absolute Deviation (MAD)2
Skewness-0.331649198
Sum609529
Variance4.471591424
MonotocityNot monotonic
2020-11-30T23:55:13.468190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
64807525.1%
 
12109711.0%
 
22011710.5%
 
7178739.3%
 
3132406.9%
 
4115386.0%
 
597535.1%
 
(Missing)4995926.1%
 
ValueCountFrequency (%) 
12109711.0%
 
22011710.5%
 
3132406.9%
 
4115386.0%
 
597535.1%
 
64807525.1%
 
7178739.3%
 
ValueCountFrequency (%) 
7178739.3%
 
64807525.1%
 
597535.1%
 
4115386.0%
 
3132406.9%
 
22011710.5%
 
12109711.0%
 

CAMEO_DEU_2015
Categorical

MISSING

Distinct45
Distinct (%)< 0.1%
Missing50428
Missing (%)26.3%
Memory size1.5 MiB
2D
11208 
6B
9634 
4C
 
9053
3D
 
8085
4A
 
7507
Other values (40)
95737 
ValueCountFrequency (%) 
2D112085.8%
 
6B96345.0%
 
4C90534.7%
 
3D80854.2%
 
4A75073.9%
 
3C66283.5%
 
1D58803.1%
 
2C50762.6%
 
5D45462.4%
 
8A42522.2%
 
1A41982.2%
 
7A41092.1%
 
8B37902.0%
 
2A37151.9%
 
2B34851.8%
 
7B34211.8%
 
1E33371.7%
 
6E30861.6%
 
6C28321.5%
 
8C28011.5%
 
1C22061.2%
 
8D22061.2%
 
4D21241.1%
 
4B20931.1%
 
5A19691.0%
 
Other values (20)2398312.5%
 
(Missing)5042826.3%
 
2020-11-30T23:55:13.582846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters18
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n10085623.3%
 
a5042811.6%
 
D380418.8%
 
C323517.5%
 
A294396.8%
 
B279666.4%
 
2234845.4%
 
4220645.1%
 
6187174.3%
 
3183904.2%
 
1167783.9%
 
8130493.0%
 
5116662.7%
 
E110742.6%
 
7105582.4%
 
963921.5%
 
F22270.5%
 
X2520.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter15128434.9%
 
Uppercase Letter14135032.6%
 
Decimal Number14109832.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
22348416.6%
 
42206415.6%
 
61871713.3%
 
31839013.0%
 
11677811.9%
 
8130499.2%
 
5116668.3%
 
7105587.5%
 
963924.5%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
D3804126.9%
 
C3235122.9%
 
A2943920.8%
 
B2796619.8%
 
E110747.8%
 
F22271.6%
 
X2520.2%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10085666.7%
 
a5042833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin29263467.5%
 
Common14109832.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
22348416.6%
 
42206415.6%
 
61871713.3%
 
31839013.0%
 
11677811.9%
 
8130499.2%
 
5116668.3%
 
7105587.5%
 
963924.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10085634.5%
 
a5042817.2%
 
D3804113.0%
 
C3235111.1%
 
A2943910.1%
 
B279669.6%
 
E110743.8%
 
F22270.8%
 
X2520.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII433732100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n10085623.3%
 
a5042811.6%
 
D380418.8%
 
C323517.5%
 
A294396.8%
 
B279666.4%
 
2234845.4%
 
4220645.1%
 
6187174.3%
 
3183904.2%
 
1167783.9%
 
8130493.0%
 
5116662.7%
 
E110742.6%
 
7105582.4%
 
963921.5%
 
F22270.5%
 
X2520.1%
 

CAMEO_DEUG_2015
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing50554
Missing (%)26.4%
Infinite0
Infinite (%)0.0%
Mean4.348963132
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:13.679937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile8
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.375612397
Coefficient of variation (CV)0.5462479962
Kurtosis-1.028594676
Mean4.348963132
Median Absolute Deviation (MAD)2
Skewness0.3075199688
Sum613630
Variance5.643534259
MonotocityNot monotonic
2020-11-30T23:55:13.760074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
22348412.3%
 
42206411.5%
 
6187179.8%
 
3183909.6%
 
1167788.8%
 
8130496.8%
 
5116666.1%
 
7105585.5%
 
963923.3%
 
(Missing)5055426.4%
 
ValueCountFrequency (%) 
1167788.8%
 
22348412.3%
 
3183909.6%
 
42206411.5%
 
5116666.1%
 
6187179.8%
 
7105585.5%
 
8130496.8%
 
963923.3%
 
ValueCountFrequency (%) 
963923.3%
 
8130496.8%
 
7105585.5%
 
6187179.8%
 
5116666.1%
 
42206411.5%
 
3183909.6%
 
22348412.3%
 
1167788.8%
 

CAMEO_INTL_2015
Real number (ℝ≥0)

MISSING

Distinct21
Distinct (%)< 0.1%
Missing50554
Missing (%)26.4%
Infinite0
Infinite (%)0.0%
Mean29.35578109
Minimum12
Maximum55
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:13.857648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile13
Q115
median24
Q343
95-th percentile54
Maximum55
Range43
Interquartile range (IQR)28

Descriptive statistics

Standard deviation13.61976101
Coefficient of variation (CV)0.4639549863
Kurtosis-1.17946671
Mean29.35578109
Median Absolute Deviation (MAD)10
Skewness0.3974334609
Sum4142042
Variance185.49789
MonotocityNot monotonic
2020-11-30T23:55:13.950476image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
141964710.3%
 
24178059.3%
 
41113205.9%
 
4396345.0%
 
2593724.9%
 
1592174.8%
 
5181134.2%
 
1376834.0%
 
2275073.9%
 
2357703.0%
 
3453682.8%
 
4552882.8%
 
5447952.5%
 
1237151.9%
 
5537141.9%
 
4428321.5%
 
3127311.4%
 
3522941.2%
 
3216960.9%
 
3315740.8%
 
5210230.5%
 
(Missing)5055426.4%
 
ValueCountFrequency (%) 
1237151.9%
 
1376834.0%
 
141964710.3%
 
1592174.8%
 
2275073.9%
 
2357703.0%
 
24178059.3%
 
2593724.9%
 
3127311.4%
 
3216960.9%
 
ValueCountFrequency (%) 
5537141.9%
 
5447952.5%
 
5210230.5%
 
5181134.2%
 
4552882.8%
 
4428321.5%
 
4396345.0%
 
41113205.9%
 
3522941.2%
 
3453682.8%
 

CJT_GESAMTTYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean3.677927605
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:14.032973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.813974805
Coefficient of variation (CV)0.4932056852
Kurtosis-1.453254602
Mean3.677927605
Median Absolute Deviation (MAD)2
Skewness0.01565975795
Sum693065
Variance3.290504592
MonotocityNot monotonic
2020-11-30T23:55:14.114576image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
65190727.1%
 
24284122.4%
 
42691214.0%
 
32434312.7%
 
12422912.6%
 
5182079.5%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
12422912.6%
 
24284122.4%
 
32434312.7%
 
42691214.0%
 
5182079.5%
 
65190727.1%
 
ValueCountFrequency (%) 
65190727.1%
 
5182079.5%
 
42691214.0%
 
32434312.7%
 
24284122.4%
 
12422912.6%
 

CJT_KATALOGNUTZER
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean4.009939556
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:14.196911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.378940266
Coefficient of variation (CV)0.3438805616
Kurtosis-0.07957104703
Mean4.009939556
Median Absolute Deviation (MAD)0
Skewness-1.148011766
Sum755629
Variance1.901476259
MonotocityNot monotonic
2020-11-30T23:55:14.278544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
510754456.1%
 
42727114.2%
 
32208711.5%
 
12051010.7%
 
2110275.8%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
12051010.7%
 
2110275.8%
 
32208711.5%
 
42727114.2%
 
510754456.1%
 
ValueCountFrequency (%) 
510754456.1%
 
42727114.2%
 
32208711.5%
 
2110275.8%
 
12051010.7%
 

CJT_TYP_1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean2.665440806
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:14.369424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.54571399
Coefficient of variation (CV)0.5799093291
Kurtosis-1.288392741
Mean2.665440806
Median Absolute Deviation (MAD)1
Skewness0.4839845256
Sum502273
Variance2.389231738
MonotocityNot monotonic
2020-11-30T23:55:14.451384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
15591629.2%
 
25336227.8%
 
54606924.0%
 
32308012.0%
 
4100125.2%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
15591629.2%
 
25336227.8%
 
32308012.0%
 
4100125.2%
 
54606924.0%
 
ValueCountFrequency (%) 
54606924.0%
 
4100125.2%
 
32308012.0%
 
25336227.8%
 
15591629.2%
 

CJT_TYP_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean2.548490493
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:14.545969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.55726248
Coefficient of variation (CV)0.6110528896
Kurtosis-1.185324929
Mean2.548490493
Median Absolute Deviation (MAD)1
Skewness0.6024492468
Sum480235
Variance2.425066431
MonotocityNot monotonic
2020-11-30T23:55:14.628446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
16471633.8%
 
25179427.0%
 
54429423.1%
 
32007910.5%
 
475563.9%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
16471633.8%
 
25179427.0%
 
32007910.5%
 
475563.9%
 
54429423.1%
 
ValueCountFrequency (%) 
54429423.1%
 
475563.9%
 
32007910.5%
 
25179427.0%
 
16471633.8%
 

CJT_TYP_3
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean4.516368692
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:14.719570image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8747222352
Coefficient of variation (CV)0.1936782169
Kurtosis2.977297277
Mean4.516368692
Median Absolute Deviation (MAD)0
Skewness-1.894197199
Sum851060
Variance0.7651389888
MonotocityNot monotonic
2020-11-30T23:55:14.802233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
513312469.5%
 
43049415.9%
 
3155648.1%
 
275153.9%
 
117420.9%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
117420.9%
 
275153.9%
 
3155648.1%
 
43049415.9%
 
513312469.5%
 
ValueCountFrequency (%) 
513312469.5%
 
43049415.9%
 
3155648.1%
 
275153.9%
 
117420.9%
 

CJT_TYP_4
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean4.415317424
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:14.892321image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.02528149
Coefficient of variation (CV)0.232210143
Kurtosis2.486947546
Mean4.415317424
Median Absolute Deviation (MAD)0
Skewness-1.832938677
Sum832018
Variance1.051202134
MonotocityNot monotonic
2020-11-30T23:55:14.978321image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
512787866.7%
 
43233916.9%
 
3119826.3%
 
2110865.8%
 
151542.7%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
151542.7%
 
2110865.8%
 
3119826.3%
 
43233916.9%
 
512787866.7%
 
ValueCountFrequency (%) 
512787866.7%
 
43233916.9%
 
3119826.3%
 
2110865.8%
 
151542.7%
 

CJT_TYP_5
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean4.51995606
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:15.068082image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.895370972
Coefficient of variation (CV)0.1980928487
Kurtosis3.171113593
Mean4.51995606
Median Absolute Deviation (MAD)0
Skewness-1.93764937
Sum851736
Variance0.8016891775
MonotocityNot monotonic
2020-11-30T23:55:15.151627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
513630971.1%
 
42485513.0%
 
3188559.8%
 
257863.0%
 
126341.4%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
126341.4%
 
257863.0%
 
3188559.8%
 
42485513.0%
 
513630971.1%
 
ValueCountFrequency (%) 
513630971.1%
 
42485513.0%
 
3188559.8%
 
257863.0%
 
126341.4%
 

CJT_TYP_6
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean4.538837502
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:15.243788image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8860911615
Coefficient of variation (CV)0.1952242532
Kurtosis3.379922262
Mean4.538837502
Median Absolute Deviation (MAD)0
Skewness-2.02193781
Sum855294
Variance0.7851575465
MonotocityNot monotonic
2020-11-30T23:55:15.328760image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
513764371.8%
 
42728214.2%
 
3127916.7%
 
288554.6%
 
118681.0%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
118681.0%
 
288554.6%
 
3127916.7%
 
42728214.2%
 
513764371.8%
 
ValueCountFrequency (%) 
513764371.8%
 
42728214.2%
 
3127916.7%
 
288554.6%
 
118681.0%
 

D19_BANKEN_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09104001002
Minimum0
Maximum6
Zeros180150
Zeros (%)94.0%
Memory size1.5 MiB
2020-11-30T23:55:15.419886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4166841409
Coefficient of variation (CV)4.57693426
Kurtosis45.05976397
Mean0.09104001002
Median Absolute Deviation (MAD)0
Skewness6.025510973
Sum17448
Variance0.1736256733
MonotocityNot monotonic
2020-11-30T23:55:15.499549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
018015094.0%
 
174503.9%
 
228361.5%
 
37010.4%
 
43790.2%
 
51090.1%
 
627< 0.1%
 
ValueCountFrequency (%) 
018015094.0%
 
174503.9%
 
228361.5%
 
37010.4%
 
43790.2%
 
51090.1%
 
627< 0.1%
 
ValueCountFrequency (%) 
627< 0.1%
 
51090.1%
 
43790.2%
 
37010.4%
 
228361.5%
 
174503.9%
 
018015094.0%
 

D19_BANKEN_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1595235114
Minimum0
Maximum6
Zeros173701
Zeros (%)90.6%
Memory size1.5 MiB
2020-11-30T23:55:15.584691image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5898238705
Coefficient of variation (CV)3.697410278
Kurtosis28.41577649
Mean0.1595235114
Median Absolute Deviation (MAD)0
Skewness4.868116602
Sum30573
Variance0.3478921983
MonotocityNot monotonic
2020-11-30T23:55:15.663488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
017370190.6%
 
1102485.3%
 
249192.6%
 
313200.7%
 
49350.5%
 
53870.2%
 
61420.1%
 
ValueCountFrequency (%) 
017370190.6%
 
1102485.3%
 
249192.6%
 
313200.7%
 
49350.5%
 
53870.2%
 
61420.1%
 
ValueCountFrequency (%) 
61420.1%
 
53870.2%
 
49350.5%
 
313200.7%
 
249192.6%
 
1102485.3%
 
017370190.6%
 

D19_BANKEN_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.367598564
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:15.752646image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.64326232
Coefficient of variation (CV)0.1754198057
Kurtosis10.03183108
Mean9.367598564
Median Absolute Deviation (MAD)0
Skewness-3.146670024
Sum1795319
Variance2.700311053
MonotocityNot monotonic
2020-11-30T23:55:15.833924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1015276279.7%
 
9148197.7%
 
564583.4%
 
861203.2%
 
632571.7%
 
731921.7%
 
119881.0%
 
411720.6%
 
211360.6%
 
37480.4%
 
ValueCountFrequency (%) 
119881.0%
 
211360.6%
 
37480.4%
 
411720.6%
 
564583.4%
 
632571.7%
 
731921.7%
 
861203.2%
 
9148197.7%
 
1015276279.7%
 
ValueCountFrequency (%) 
1015276279.7%
 
9148197.7%
 
861203.2%
 
731921.7%
 
632571.7%
 
564583.4%
 
411720.6%
 
37480.4%
 
211360.6%
 
119881.0%
 

D19_BANKEN_DIREKT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6461659675
Minimum0
Maximum7
Zeros166726
Zeros (%)87.0%
Memory size1.5 MiB
2020-11-30T23:55:15.919419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.771524943
Coefficient of variation (CV)2.741594315
Kurtosis4.988131207
Mean0.6461659675
Median Absolute Deviation (MAD)0
Skewness2.570975647
Sum123839
Variance3.138300623
MonotocityNot monotonic
2020-11-30T23:55:16.002670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
016672687.0%
 
6118026.2%
 
348842.5%
 
526841.4%
 
725161.3%
 
211440.6%
 
410530.5%
 
18430.4%
 
ValueCountFrequency (%) 
016672687.0%
 
18430.4%
 
211440.6%
 
348842.5%
 
410530.5%
 
526841.4%
 
6118026.2%
 
725161.3%
 
ValueCountFrequency (%) 
725161.3%
 
6118026.2%
 
526841.4%
 
410530.5%
 
348842.5%
 
211440.6%
 
18430.4%
 
016672687.0%
 

D19_BANKEN_GROSS
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4244776992
Minimum0
Maximum6
Zeros175064
Zeros (%)91.3%
Memory size1.5 MiB
2020-11-30T23:55:16.091505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.443738888
Coefficient of variation (CV)3.401212575
Kurtosis9.211679916
Mean0.4244776992
Median Absolute Deviation (MAD)0
Skewness3.287695646
Sum81352
Variance2.084381977
MonotocityNot monotonic
2020-11-30T23:55:16.170585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
017506491.3%
 
690974.7%
 
330401.6%
 
524881.3%
 
48750.5%
 
26220.3%
 
14660.2%
 
ValueCountFrequency (%) 
017506491.3%
 
14660.2%
 
26220.3%
 
330401.6%
 
48750.5%
 
524881.3%
 
690974.7%
 
ValueCountFrequency (%) 
690974.7%
 
524881.3%
 
48750.5%
 
330401.6%
 
26220.3%
 
14660.2%
 
017506491.3%
 

D19_BANKEN_LOKAL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1329701751
Minimum0
Maximum7
Zeros187347
Zeros (%)97.8%
Memory size1.5 MiB
2020-11-30T23:55:16.256776image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9079254017
Coefficient of variation (CV)6.828037948
Kurtosis47.40494858
Mean0.1329701751
Median Absolute Deviation (MAD)0
Skewness6.951105176
Sum25484
Variance0.824328535
MonotocityNot monotonic
2020-11-30T23:55:16.339907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
018734797.8%
 
724551.3%
 
38330.4%
 
67880.4%
 
52030.1%
 
222< 0.1%
 
43< 0.1%
 
11< 0.1%
 
ValueCountFrequency (%) 
018734797.8%
 
11< 0.1%
 
222< 0.1%
 
38330.4%
 
43< 0.1%
 
52030.1%
 
67880.4%
 
724551.3%
 
ValueCountFrequency (%) 
724551.3%
 
67880.4%
 
52030.1%
 
43< 0.1%
 
38330.4%
 
222< 0.1%
 
11< 0.1%
 
018734797.8%
 

D19_BANKEN_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.866471521
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:16.431706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7722532224
Coefficient of variation (CV)0.07827045573
Kurtosis48.23036322
Mean9.866471521
Median Absolute Deviation (MAD)0
Skewness-6.693493873
Sum1890929
Variance0.5963750395
MonotocityNot monotonic
2020-11-30T23:55:16.514991image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1018420296.1%
 
529591.5%
 
823281.2%
 
914140.7%
 
22770.1%
 
62440.1%
 
187< 0.1%
 
472< 0.1%
 
741< 0.1%
 
328< 0.1%
 
ValueCountFrequency (%) 
187< 0.1%
 
22770.1%
 
328< 0.1%
 
472< 0.1%
 
529591.5%
 
62440.1%
 
741< 0.1%
 
823281.2%
 
914140.7%
 
1018420296.1%
 
ValueCountFrequency (%) 
1018420296.1%
 
914140.7%
 
823281.2%
 
741< 0.1%
 
62440.1%
 
529591.5%
 
472< 0.1%
 
328< 0.1%
 
22770.1%
 
187< 0.1%
 

D19_BANKEN_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.600645962
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:16.601981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.379280426
Coefficient of variation (CV)0.1436653774
Kurtosis19.49307895
Mean9.600645962
Median Absolute Deviation (MAD)0
Skewness-4.295434337
Sum1839983
Variance1.902414493
MonotocityNot monotonic
2020-11-30T23:55:16.683086image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1016758587.4%
 
996225.0%
 
831371.6%
 
529121.5%
 
724731.3%
 
620411.1%
 
117380.9%
 
48640.5%
 
27120.4%
 
35680.3%
 
ValueCountFrequency (%) 
117380.9%
 
27120.4%
 
35680.3%
 
48640.5%
 
529121.5%
 
620411.1%
 
724731.3%
 
831371.6%
 
996225.0%
 
1016758587.4%
 
ValueCountFrequency (%) 
1016758587.4%
 
996225.0%
 
831371.6%
 
724731.3%
 
620411.1%
 
529121.5%
 
48640.5%
 
35680.3%
 
27120.4%
 
117380.9%
 

D19_BANKEN_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct10
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Infinite0
Infinite (%)0.0%
Mean0.4620193811
Minimum0
Maximum10
Zeros137161
Zeros (%)71.6%
Memory size1.5 MiB
2020-11-30T23:55:16.770043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.087401901
Coefficient of variation (CV)4.517996402
Kurtosis16.72476778
Mean0.4620193811
Median Absolute Deviation (MAD)0
Skewness4.320566308
Sum66510
Variance4.357246697
MonotocityNot monotonic
2020-11-30T23:55:16.857379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
013716171.6%
 
1064633.4%
 
51400.1%
 
782< 0.1%
 
344< 0.1%
 
838< 0.1%
 
914< 0.1%
 
28< 0.1%
 
64< 0.1%
 
41< 0.1%
 
(Missing)4769724.9%
 
ValueCountFrequency (%) 
013716171.6%
 
28< 0.1%
 
344< 0.1%
 
41< 0.1%
 
51400.1%
 
64< 0.1%
 
782< 0.1%
 
838< 0.1%
 
914< 0.1%
 
1064633.4%
 
ValueCountFrequency (%) 
1064633.4%
 
914< 0.1%
 
838< 0.1%
 
782< 0.1%
 
64< 0.1%
 
51400.1%
 
41< 0.1%
 
344< 0.1%
 
28< 0.1%
 
013716171.6%
 

D19_BANKEN_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4444774905
Minimum0
Maximum7
Zeros176243
Zeros (%)92.0%
Memory size1.5 MiB
2020-11-30T23:55:16.944427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.546226218
Coefficient of variation (CV)3.478750334
Kurtosis9.193731425
Mean0.4444774905
Median Absolute Deviation (MAD)0
Skewness3.304743405
Sum85185
Variance2.390815519
MonotocityNot monotonic
2020-11-30T23:55:17.026079image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
017624392.0%
 
696205.0%
 
718291.0%
 
516430.9%
 
315590.8%
 
24000.2%
 
42040.1%
 
11540.1%
 
ValueCountFrequency (%) 
017624392.0%
 
11540.1%
 
24000.2%
 
315590.8%
 
42040.1%
 
516430.9%
 
696205.0%
 
718291.0%
 
ValueCountFrequency (%) 
718291.0%
 
696205.0%
 
516430.9%
 
42040.1%
 
315590.8%
 
24000.2%
 
11540.1%
 
017624392.0%
 

D19_BEKLEIDUNG_GEH
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9787270678
Minimum0
Maximum7
Zeros154242
Zeros (%)80.5%
Memory size1.5 MiB
2020-11-30T23:55:17.114077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.097214522
Coefficient of variation (CV)2.142798121
Kurtosis1.64052231
Mean0.9787270678
Median Absolute Deviation (MAD)0
Skewness1.836276363
Sum187575
Variance4.39830875
MonotocityNot monotonic
2020-11-30T23:55:17.196979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
015424280.5%
 
6181549.5%
 
378384.1%
 
555152.9%
 
729481.5%
 
213490.7%
 
48740.5%
 
17320.4%
 
ValueCountFrequency (%) 
015424280.5%
 
17320.4%
 
213490.7%
 
378384.1%
 
48740.5%
 
555152.9%
 
6181549.5%
 
729481.5%
 
ValueCountFrequency (%) 
729481.5%
 
6181549.5%
 
555152.9%
 
48740.5%
 
378384.1%
 
213490.7%
 
17320.4%
 
015424280.5%
 

D19_BEKLEIDUNG_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.527779517
Minimum0
Maximum7
Zeros137848
Zeros (%)71.9%
Memory size1.5 MiB
2020-11-30T23:55:17.303533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.562741055
Coefficient of variation (CV)1.677428599
Kurtosis-0.4473246664
Mean1.527779517
Median Absolute Deviation (MAD)0
Skewness1.186852035
Sum292802
Variance6.567641713
MonotocityNot monotonic
2020-11-30T23:55:18.746630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
013784871.9%
 
63157116.5%
 
778804.1%
 
367493.5%
 
540742.1%
 
215550.8%
 
111370.6%
 
48380.4%
 
ValueCountFrequency (%) 
013784871.9%
 
111370.6%
 
215550.8%
 
367493.5%
 
48380.4%
 
540742.1%
 
63157116.5%
 
778804.1%
 
ValueCountFrequency (%) 
778804.1%
 
63157116.5%
 
540742.1%
 
48380.4%
 
367493.5%
 
215550.8%
 
111370.6%
 
013784871.9%
 

D19_BILDUNG
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9985651076
Minimum0
Maximum7
Zeros155747
Zeros (%)81.3%
Memory size1.5 MiB
2020-11-30T23:55:18.842160image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.215235176
Coefficient of variation (CV)2.218418367
Kurtosis1.900404957
Mean0.9985651076
Median Absolute Deviation (MAD)0
Skewness1.920619252
Sum191377
Variance4.907266883
MonotocityNot monotonic
2020-11-30T23:55:18.950587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
015574781.3%
 
6172219.0%
 
786614.5%
 
253932.8%
 
323011.2%
 
514000.7%
 
46020.3%
 
13270.2%
 
ValueCountFrequency (%) 
015574781.3%
 
13270.2%
 
253932.8%
 
323011.2%
 
46020.3%
 
514000.7%
 
6172219.0%
 
786614.5%
 
ValueCountFrequency (%) 
786614.5%
 
6172219.0%
 
514000.7%
 
46020.3%
 
323011.2%
 
253932.8%
 
13270.2%
 
015574781.3%
 

D19_BIO_OEKO
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5384916411
Minimum0
Maximum7
Zeros174542
Zeros (%)91.1%
Memory size1.5 MiB
2020-11-30T23:55:19.046416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.74644807
Coefficient of variation (CV)3.243222247
Kurtosis7.213871093
Mean0.5384916411
Median Absolute Deviation (MAD)0
Skewness3.005302448
Sum103203
Variance3.050080861
MonotocityNot monotonic
2020-11-30T23:55:19.128618image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
017454291.1%
 
694234.9%
 
753512.8%
 
311800.6%
 
511030.6%
 
425< 0.1%
 
225< 0.1%
 
13< 0.1%
 
ValueCountFrequency (%) 
017454291.1%
 
13< 0.1%
 
225< 0.1%
 
311800.6%
 
425< 0.1%
 
511030.6%
 
694234.9%
 
753512.8%
 
ValueCountFrequency (%) 
753512.8%
 
694234.9%
 
511030.6%
 
425< 0.1%
 
311800.6%
 
225< 0.1%
 
13< 0.1%
 
017454291.1%
 

D19_BUCH_CD
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.443987018
Minimum0
Maximum7
Zeros102937
Zeros (%)53.7%
Memory size1.5 MiB
2020-11-30T23:55:19.217907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.822639395
Coefficient of variation (CV)1.154932238
Kurtosis-1.738895896
Mean2.443987018
Median Absolute Deviation (MAD)0
Skewness0.3960911885
Sum468395
Variance7.967293156
MonotocityNot monotonic
2020-11-30T23:55:19.296914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
010293753.7%
 
66321633.0%
 
380644.2%
 
547632.5%
 
143262.3%
 
730741.6%
 
229201.5%
 
423521.2%
 
ValueCountFrequency (%) 
010293753.7%
 
143262.3%
 
229201.5%
 
380644.2%
 
423521.2%
 
547632.5%
 
66321633.0%
 
730741.6%
 
ValueCountFrequency (%) 
730741.6%
 
66321633.0%
 
547632.5%
 
423521.2%
 
380644.2%
 
229201.5%
 
143262.3%
 
010293753.7%
 

D19_DIGIT_SERV
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2182653977
Minimum0
Maximum7
Zeros183539
Zeros (%)95.8%
Memory size1.5 MiB
2020-11-30T23:55:19.383057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.084784513
Coefficient of variation (CV)4.970025137
Kurtosis24.14842848
Mean0.2182653977
Median Absolute Deviation (MAD)0
Skewness5.029803628
Sum41831
Variance1.17675744
MonotocityNot monotonic
2020-11-30T23:55:19.474774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
018353995.8%
 
642332.2%
 
315820.8%
 
79220.5%
 
57650.4%
 
24340.2%
 
41210.1%
 
156< 0.1%
 
ValueCountFrequency (%) 
018353995.8%
 
156< 0.1%
 
24340.2%
 
315820.8%
 
41210.1%
 
57650.4%
 
642332.2%
 
79220.5%
 
ValueCountFrequency (%) 
79220.5%
 
642332.2%
 
57650.4%
 
41210.1%
 
315820.8%
 
24340.2%
 
156< 0.1%
 
018353995.8%
 

D19_DROGERIEARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.757998873
Minimum0
Maximum7
Zeros160837
Zeros (%)83.9%
Memory size1.5 MiB
2020-11-30T23:55:19.569638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.85788388
Coefficient of variation (CV)2.451037787
Kurtosis3.551151404
Mean0.757998873
Median Absolute Deviation (MAD)0
Skewness2.266085638
Sum145272
Variance3.451732512
MonotocityNot monotonic
2020-11-30T23:55:19.653411image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
016083783.9%
 
6119276.2%
 
363133.3%
 
544312.3%
 
726781.4%
 
421301.1%
 
220141.1%
 
113220.7%
 
ValueCountFrequency (%) 
016083783.9%
 
113220.7%
 
220141.1%
 
363133.3%
 
421301.1%
 
544312.3%
 
6119276.2%
 
726781.4%
 
ValueCountFrequency (%) 
726781.4%
 
6119276.2%
 
544312.3%
 
421301.1%
 
363133.3%
 
220141.1%
 
113220.7%
 
016083783.9%
 

D19_ENERGIE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4742658569
Minimum0
Maximum7
Zeros172916
Zeros (%)90.2%
Memory size1.5 MiB
2020-11-30T23:55:19.744803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.52271566
Coefficient of variation (CV)3.210679492
Kurtosis8.562474788
Mean0.4742658569
Median Absolute Deviation (MAD)0
Skewness3.152478177
Sum90894
Variance2.318662982
MonotocityNot monotonic
2020-11-30T23:55:19.842432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
017291690.2%
 
668593.6%
 
353642.8%
 
531251.6%
 
721661.1%
 
26970.4%
 
43140.2%
 
12110.1%
 
ValueCountFrequency (%) 
017291690.2%
 
12110.1%
 
26970.4%
 
353642.8%
 
43140.2%
 
531251.6%
 
668593.6%
 
721661.1%
 
ValueCountFrequency (%) 
721661.1%
 
668593.6%
 
531251.6%
 
43140.2%
 
353642.8%
 
26970.4%
 
12110.1%
 
017291690.2%
 

D19_FREIZEIT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6884144178
Minimum0
Maximum7
Zeros166363
Zeros (%)86.8%
Memory size1.5 MiB
2020-11-30T23:55:19.940193image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.838986968
Coefficient of variation (CV)2.67133709
Kurtosis4.252870867
Mean0.6884144178
Median Absolute Deviation (MAD)0
Skewness2.441847599
Sum131936
Variance3.381873068
MonotocityNot monotonic
2020-11-30T23:55:20.023287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
016636386.8%
 
6132756.9%
 
343612.3%
 
534151.8%
 
724481.3%
 
48490.4%
 
26550.3%
 
12860.1%
 
ValueCountFrequency (%) 
016636386.8%
 
12860.1%
 
26550.3%
 
343612.3%
 
48490.4%
 
534151.8%
 
6132756.9%
 
724481.3%
 
ValueCountFrequency (%) 
724481.3%
 
6132756.9%
 
534151.8%
 
48490.4%
 
343612.3%
 
26550.3%
 
12860.1%
 
016636386.8%
 

D19_GARTEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3445254941
Minimum0
Maximum7
Zeros179969
Zeros (%)93.9%
Memory size1.5 MiB
2020-11-30T23:55:20.112688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.383708292
Coefficient of variation (CV)4.016272572
Kurtosis13.52401246
Mean0.3445254941
Median Absolute Deviation (MAD)0
Skewness3.891901155
Sum66029
Variance1.914648638
MonotocityNot monotonic
2020-11-30T23:55:20.195029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
017996993.9%
 
663303.3%
 
721761.1%
 
516550.9%
 
313190.7%
 
4990.1%
 
285< 0.1%
 
119< 0.1%
 
ValueCountFrequency (%) 
017996993.9%
 
119< 0.1%
 
285< 0.1%
 
313190.7%
 
4990.1%
 
516550.9%
 
663303.3%
 
721761.1%
 
ValueCountFrequency (%) 
721761.1%
 
663303.3%
 
516550.9%
 
4990.1%
 
313190.7%
 
285< 0.1%
 
119< 0.1%
 
017996993.9%
 

D19_GESAMT_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9376787093
Minimum0
Maximum6
Zeros111999
Zeros (%)58.4%
Memory size1.5 MiB
2020-11-30T23:55:20.283030image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.376459195
Coefficient of variation (CV)1.467943317
Kurtosis1.195739304
Mean0.9376787093
Median Absolute Deviation (MAD)0
Skewness1.441028864
Sum179708
Variance1.894639916
MonotocityNot monotonic
2020-11-30T23:55:20.358941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
011199958.4%
 
12777714.5%
 
22506913.1%
 
3110485.8%
 
4108825.7%
 
541412.2%
 
67360.4%
 
ValueCountFrequency (%) 
011199958.4%
 
12777714.5%
 
22506913.1%
 
3110485.8%
 
4108825.7%
 
541412.2%
 
67360.4%
 
ValueCountFrequency (%) 
67360.4%
 
541412.2%
 
4108825.7%
 
3110485.8%
 
22506913.1%
 
12777714.5%
 
011199958.4%
 

D19_GESAMT_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.438581387
Minimum0
Maximum6
Zeros91722
Zeros (%)47.9%
Memory size1.5 MiB
2020-11-30T23:55:20.444046image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.742773839
Coefficient of variation (CV)1.211453071
Kurtosis-0.2757674674
Mean1.438581387
Median Absolute Deviation (MAD)1
Skewness0.9619164175
Sum275707
Variance3.037260654
MonotocityNot monotonic
2020-11-30T23:55:20.519497image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
09172247.9%
 
22773614.5%
 
12426012.7%
 
4177719.3%
 
3150457.9%
 
5109525.7%
 
641662.2%
 
ValueCountFrequency (%) 
09172247.9%
 
12426012.7%
 
22773614.5%
 
3150457.9%
 
4177719.3%
 
5109525.7%
 
641662.2%
 
ValueCountFrequency (%) 
641662.2%
 
5109525.7%
 
4177719.3%
 
3150457.9%
 
22773614.5%
 
12426012.7%
 
09172247.9%
 

D19_GESAMT_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.52949617
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:20.603837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.246551658
Coefficient of variation (CV)0.4972131958
Kurtosis-1.30427266
Mean6.52949617
Median Absolute Deviation (MAD)3
Skewness-0.3805784073
Sum1251391
Variance10.54009767
MonotocityNot monotonic
2020-11-30T23:55:20.683434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
106053631.6%
 
52547713.3%
 
11962610.2%
 
91907110.0%
 
2149817.8%
 
8121156.3%
 
6113135.9%
 
4111665.8%
 
789644.7%
 
384034.4%
 
ValueCountFrequency (%) 
11962610.2%
 
2149817.8%
 
384034.4%
 
4111665.8%
 
52547713.3%
 
6113135.9%
 
789644.7%
 
8121156.3%
 
91907110.0%
 
106053631.6%
 
ValueCountFrequency (%) 
106053631.6%
 
91907110.0%
 
8121156.3%
 
789644.7%
 
6113135.9%
 
52547713.3%
 
4111665.8%
 
384034.4%
 
2149817.8%
 
11962610.2%
 

D19_GESAMT_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.412435039
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:20.776287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q18
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.18512237
Coefficient of variation (CV)0.2597490928
Kurtosis1.701849686
Mean8.412435039
Median Absolute Deviation (MAD)1
Skewness-1.550164165
Sum1612260
Variance4.774759771
MonotocityNot monotonic
2020-11-30T23:55:20.871998image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
108929646.6%
 
93697719.3%
 
82097310.9%
 
5150327.8%
 
793134.9%
 
679424.1%
 
236731.9%
 
434041.8%
 
126841.4%
 
323581.2%
 
ValueCountFrequency (%) 
126841.4%
 
236731.9%
 
323581.2%
 
434041.8%
 
5150327.8%
 
679424.1%
 
793134.9%
 
82097310.9%
 
93697719.3%
 
108929646.6%
 
ValueCountFrequency (%) 
108929646.6%
 
93697719.3%
 
82097310.9%
 
793134.9%
 
679424.1%
 
5150327.8%
 
434041.8%
 
323581.2%
 
236731.9%
 
126841.4%
 

D19_GESAMT_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.445714107
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:20.983561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.117772196
Coefficient of variation (CV)0.4187338046
Kurtosis-0.7243027577
Mean7.445714107
Median Absolute Deviation (MAD)1
Skewness-0.8570109421
Sum1426986
Variance9.720503465
MonotocityNot monotonic
2020-11-30T23:55:21.074519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
108984046.9%
 
5186529.7%
 
9182039.5%
 
1142077.4%
 
296275.0%
 
894354.9%
 
693134.9%
 
485394.5%
 
777544.0%
 
360823.2%
 
ValueCountFrequency (%) 
1142077.4%
 
296275.0%
 
360823.2%
 
485394.5%
 
5186529.7%
 
693134.9%
 
777544.0%
 
894354.9%
 
9182039.5%
 
108984046.9%
 
ValueCountFrequency (%) 
108984046.9%
 
9182039.5%
 
894354.9%
 
777544.0%
 
693134.9%
 
5186529.7%
 
485394.5%
 
360823.2%
 
296275.0%
 
1142077.4%
 

D19_GESAMT_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Infinite0
Infinite (%)0.0%
Mean3.522878677
Minimum0
Maximum10
Zeros86879
Zeros (%)45.3%
Memory size1.5 MiB
2020-11-30T23:55:21.176210image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q310
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)10

Descriptive statistics

Standard deviation4.561253201
Coefficient of variation (CV)1.294751713
Kurtosis-1.547743994
Mean3.522878677
Median Absolute Deviation (MAD)0
Skewness0.6049669116
Sum507136
Variance20.80503077
MonotocityNot monotonic
2020-11-30T23:55:21.277825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
08687945.3%
 
104219122.0%
 
540102.1%
 
826771.4%
 
723921.2%
 
317670.9%
 
915020.8%
 
27010.4%
 
66660.3%
 
16270.3%
 
45430.3%
 
(Missing)4769724.9%
 
ValueCountFrequency (%) 
08687945.3%
 
16270.3%
 
27010.4%
 
317670.9%
 
45430.3%
 
540102.1%
 
66660.3%
 
723921.2%
 
826771.4%
 
915020.8%
 
ValueCountFrequency (%) 
104219122.0%
 
915020.8%
 
826771.4%
 
723921.2%
 
66660.3%
 
540102.1%
 
45430.3%
 
317670.9%
 
27010.4%
 
16270.3%
 

D19_HANDWERK
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.535256611
Minimum0
Maximum7
Zeros143537
Zeros (%)74.9%
Memory size1.5 MiB
2020-11-30T23:55:21.380114image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.668879944
Coefficient of variation (CV)1.73839339
Kurtosis-0.5466882006
Mean1.535256611
Median Absolute Deviation (MAD)0
Skewness1.186063581
Sum294235
Variance7.122920157
MonotocityNot monotonic
2020-11-30T23:55:21.486945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
014353774.9%
 
63712519.4%
 
791534.8%
 
59540.5%
 
38210.4%
 
431< 0.1%
 
226< 0.1%
 
15< 0.1%
 
ValueCountFrequency (%) 
014353774.9%
 
15< 0.1%
 
226< 0.1%
 
38210.4%
 
431< 0.1%
 
59540.5%
 
63712519.4%
 
791534.8%
 
ValueCountFrequency (%) 
791534.8%
 
63712519.4%
 
59540.5%
 
431< 0.1%
 
38210.4%
 
226< 0.1%
 
15< 0.1%
 
014353774.9%
 

D19_HAUS_DEKO
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.53703066
Minimum0
Maximum7
Zeros132811
Zeros (%)69.3%
Memory size1.5 MiB
2020-11-30T23:55:21.602443image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.459250091
Coefficient of variation (CV)1.600000674
Kurtosis-0.5493058082
Mean1.53703066
Median Absolute Deviation (MAD)0
Skewness1.121730654
Sum294575
Variance6.047911012
MonotocityNot monotonic
2020-11-30T23:55:21.698988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
013281169.3%
 
63260017.0%
 
3112915.9%
 
568513.6%
 
727191.4%
 
227081.4%
 
114300.7%
 
412420.6%
 
ValueCountFrequency (%) 
013281169.3%
 
114300.7%
 
227081.4%
 
3112915.9%
 
412420.6%
 
568513.6%
 
63260017.0%
 
727191.4%
 
ValueCountFrequency (%) 
727191.4%
 
63260017.0%
 
568513.6%
 
412420.6%
 
3112915.9%
 
227081.4%
 
114300.7%
 
013281169.3%
 

D19_KINDERARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.083515956
Minimum0
Maximum7
Zeros153651
Zeros (%)80.2%
Memory size1.5 MiB
2020-11-30T23:55:21.806112image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.277333103
Coefficient of variation (CV)2.101799323
Kurtosis1.237898453
Mean1.083515956
Median Absolute Deviation (MAD)0
Skewness1.745927238
Sum207658
Variance5.18624606
MonotocityNot monotonic
2020-11-30T23:55:21.910808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
015365180.2%
 
61966210.3%
 
775854.0%
 
347232.5%
 
531251.6%
 
217700.9%
 
47070.4%
 
14290.2%
 
ValueCountFrequency (%) 
015365180.2%
 
14290.2%
 
217700.9%
 
347232.5%
 
47070.4%
 
531251.6%
 
61966210.3%
 
775854.0%
 
ValueCountFrequency (%) 
775854.0%
 
61966210.3%
 
531251.6%
 
47070.4%
 
347232.5%
 
217700.9%
 
14290.2%
 
015365180.2%
 

D19_KONSUMTYP
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Infinite0
Infinite (%)0.0%
Mean3.027654475
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:22.021308image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.206506896
Coefficient of variation (CV)0.7287842501
Kurtosis2.031475141
Mean3.027654475
Median Absolute Deviation (MAD)1
Skewness1.646762171
Sum435846
Variance4.868672684
MonotocityNot monotonic
2020-11-30T23:55:22.122556image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
35232327.3%
 
13579418.7%
 
22960015.4%
 
9125166.5%
 
674243.9%
 
447952.5%
 
515030.8%
 
(Missing)4769724.9%
 
ValueCountFrequency (%) 
13579418.7%
 
22960015.4%
 
35232327.3%
 
447952.5%
 
515030.8%
 
674243.9%
 
9125166.5%
 
ValueCountFrequency (%) 
9125166.5%
 
674243.9%
 
515030.8%
 
447952.5%
 
35232327.3%
 
22960015.4%
 
13579418.7%
 

D19_KONSUMTYP_MAX
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.224469351
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:22.221381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q38
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.198298122
Coefficient of variation (CV)0.7570887267
Kurtosis-1.400897755
Mean4.224469351
Median Absolute Deviation (MAD)1
Skewness0.6773018872
Sum809628
Variance10.22911088
MonotocityNot monotonic
2020-11-30T23:55:22.316276image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
29175847.9%
 
94769724.9%
 
12007510.5%
 
8139117.3%
 
4108435.7%
 
373683.8%
 
ValueCountFrequency (%) 
12007510.5%
 
29175847.9%
 
373683.8%
 
4108435.7%
 
8139117.3%
 
94769724.9%
 
ValueCountFrequency (%) 
94769724.9%
 
8139117.3%
 
4108435.7%
 
373683.8%
 
29175847.9%
 
12007510.5%
 

D19_KOSMETIK
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.756110033
Minimum0
Maximum7
Zeros139367
Zeros (%)72.7%
Memory size1.5 MiB
2020-11-30T23:55:22.420877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.883393243
Coefficient of variation (CV)1.641920602
Kurtosis-0.8435883915
Mean1.756110033
Median Absolute Deviation (MAD)0
Skewness1.054458807
Sum336562
Variance8.313956594
MonotocityNot monotonic
2020-11-30T23:55:22.515667image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
013936772.7%
 
62749714.3%
 
72419312.6%
 
32680.1%
 
52340.1%
 
248< 0.1%
 
438< 0.1%
 
17< 0.1%
 
ValueCountFrequency (%) 
013936772.7%
 
17< 0.1%
 
248< 0.1%
 
32680.1%
 
438< 0.1%
 
52340.1%
 
62749714.3%
 
72419312.6%
 
ValueCountFrequency (%) 
72419312.6%
 
62749714.3%
 
52340.1%
 
438< 0.1%
 
32680.1%
 
248< 0.1%
 
17< 0.1%
 
013936772.7%
 

D19_LEBENSMITTEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.577635506
Minimum0
Maximum7
Zeros170971
Zeros (%)89.2%
Memory size1.5 MiB
2020-11-30T23:55:22.619759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.723675155
Coefficient of variation (CV)2.984018706
Kurtosis6.156141266
Mean0.577635506
Median Absolute Deviation (MAD)0
Skewness2.798068542
Sum110705
Variance2.971056041
MonotocityNot monotonic
2020-11-30T23:55:22.722698image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
017097189.2%
 
6108085.6%
 
339312.1%
 
729781.6%
 
523611.2%
 
23570.2%
 
41510.1%
 
195< 0.1%
 
ValueCountFrequency (%) 
017097189.2%
 
195< 0.1%
 
23570.2%
 
339312.1%
 
41510.1%
 
523611.2%
 
6108085.6%
 
729781.6%
 
ValueCountFrequency (%) 
729781.6%
 
6108085.6%
 
523611.2%
 
41510.1%
 
339312.1%
 
23570.2%
 
195< 0.1%
 
017097189.2%
 

D19_LETZTER_KAUF_BRANCHE
Categorical

MISSING

Distinct35
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Memory size1.5 MiB
D19_UNBEKANNT
31910 
D19_SONSTIGE
14540 
D19_VERSICHERUNGEN
10534 
D19_BUCH_CD
10038 
D19_VOLLSORTIMENT
8647 
Other values (30)
68286 
ValueCountFrequency (%) 
D19_UNBEKANNT3191016.6%
 
D19_SONSTIGE145407.6%
 
D19_VERSICHERUNGEN105345.5%
 
D19_BUCH_CD100385.2%
 
D19_VOLLSORTIMENT86474.5%
 
D19_HAUS_DEKO81294.2%
 
D19_SCHUHE63173.3%
 
D19_BEKLEIDUNG_GEH59753.1%
 
D19_DROGERIEARTIKEL55282.9%
 
D19_ENERGIE44542.3%
 
D19_BEKLEIDUNG_REST40962.1%
 
D19_VERSAND_REST36191.9%
 
D19_BANKEN_DIREKT34661.8%
 
D19_LEBENSMITTEL30531.6%
 
D19_TELKO_REST23031.2%
 
D19_NAHRUNGSERGAENZUNG22531.2%
 
D19_TELKO_MOBILE21311.1%
 
D19_TECHNIK18361.0%
 
D19_BANKEN_GROSS16840.9%
 
D19_FREIZEIT16720.9%
 
D19_SAMMELARTIKEL16100.8%
 
D19_RATGEBER15190.8%
 
D19_KINDERARTIKEL14390.8%
 
D19_WEIN_FEINKOST14240.7%
 
D19_BANKEN_REST12330.6%
 
Other values (10)45452.4%
 
(Missing)4769724.9%
 
2020-11-30T23:55:22.866698image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters26
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E22432610.2%
 
N1918188.7%
 
_1898208.6%
 
D1877878.5%
 
11439556.5%
 
91439556.5%
 
T1064444.8%
 
n953944.3%
 
S907204.1%
 
R875864.0%
 
I844113.8%
 
U818623.7%
 
K801983.6%
 
A683103.1%
 
B665763.0%
 
G626422.8%
 
O583982.6%
 
H519312.4%
 
L517312.3%
 
a476972.2%
 
C387631.8%
 
V234531.1%
 
M171670.8%
 
Z39250.2%
 
F30960.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter158310071.8%
 
Decimal Number28791013.1%
 
Connector Punctuation1898208.6%
 
Lowercase Letter1430916.5%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E22432614.2%
 
N19181812.1%
 
D18778711.9%
 
T1064446.7%
 
S907205.7%
 
R875865.5%
 
I844115.3%
 
U818625.2%
 
K801985.1%
 
A683104.3%
 
B665764.2%
 
G626424.0%
 
O583983.7%
 
H519313.3%
 
L517313.3%
 
C387632.4%
 
V234531.5%
 
M171671.1%
 
Z39250.2%
 
F30960.2%
 
W19560.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
114395550.0%
 
914395550.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_189820100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n9539466.7%
 
a4769733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin172619178.3%
 
Common47773021.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E22432613.0%
 
N19181811.1%
 
D18778710.9%
 
T1064446.2%
 
n953945.5%
 
S907205.3%
 
R875865.1%
 
I844114.9%
 
U818624.7%
 
K801984.6%
 
A683104.0%
 
B665763.9%
 
G626423.6%
 
O583983.4%
 
H519313.0%
 
L517313.0%
 
a476972.8%
 
C387632.2%
 
V234531.4%
 
M171671.0%
 
Z39250.2%
 
F30960.2%
 
W19560.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
_18982039.7%
 
114395530.1%
 
914395530.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2203921100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E22432610.2%
 
N1918188.7%
 
_1898208.6%
 
D1877878.5%
 
11439556.5%
 
91439556.5%
 
T1064444.8%
 
n953944.3%
 
S907204.1%
 
R875864.0%
 
I844113.8%
 
U818623.7%
 
K801983.6%
 
A683103.1%
 
B665763.0%
 
G626422.8%
 
O583982.6%
 
H519312.4%
 
L517312.3%
 
a476972.2%
 
C387631.8%
 
V234531.1%
 
M171670.8%
 
Z39250.2%
 
F30960.1%
 

D19_LOTTO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct8
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Infinite0
Infinite (%)0.0%
Mean2.633732764
Minimum0
Maximum7
Zeros88281
Zeros (%)46.1%
Memory size1.5 MiB
2020-11-30T23:55:22.992980image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.332828243
Coefficient of variation (CV)1.265439033
Kurtosis-1.741519834
Mean2.633732764
Median Absolute Deviation (MAD)0
Skewness0.4884701068
Sum379139
Variance11.1077441
MonotocityNot monotonic
2020-11-30T23:55:23.078508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
08828146.1%
 
74708424.6%
 
676094.0%
 
54810.3%
 
34680.2%
 
217< 0.1%
 
413< 0.1%
 
12< 0.1%
 
(Missing)4769724.9%
 
ValueCountFrequency (%) 
08828146.1%
 
12< 0.1%
 
217< 0.1%
 
34680.2%
 
413< 0.1%
 
54810.3%
 
676094.0%
 
74708424.6%
 
ValueCountFrequency (%) 
74708424.6%
 
676094.0%
 
54810.3%
 
413< 0.1%
 
34680.2%
 
217< 0.1%
 
12< 0.1%
 
08828146.1%
 

D19_NAHRUNGSERGAENZUNG
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5059169745
Minimum0
Maximum7
Zeros174094
Zeros (%)90.8%
Memory size1.5 MiB
2020-11-30T23:55:23.174180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.651735897
Coefficient of variation (CV)3.264835893
Kurtosis7.966241302
Mean0.5059169745
Median Absolute Deviation (MAD)0
Skewness3.102989701
Sum96960
Variance2.728231474
MonotocityNot monotonic
2020-11-30T23:55:23.272192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
017409490.8%
 
682254.3%
 
740392.1%
 
325841.3%
 
520351.1%
 
22850.1%
 
12400.1%
 
41500.1%
 
ValueCountFrequency (%) 
017409490.8%
 
12400.1%
 
22850.1%
 
325841.3%
 
41500.1%
 
520351.1%
 
682254.3%
 
740392.1%
 
ValueCountFrequency (%) 
740392.1%
 
682254.3%
 
520351.1%
 
41500.1%
 
325841.3%
 
22850.1%
 
12400.1%
 
017409490.8%
 

D19_RATGEBER
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.799756851
Minimum0
Maximum7
Zeros161270
Zeros (%)84.1%
Memory size1.5 MiB
2020-11-30T23:55:23.384715image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.959001155
Coefficient of variation (CV)2.449495935
Kurtosis3.207414088
Mean0.799756851
Median Absolute Deviation (MAD)0
Skewness2.218221165
Sum153275
Variance3.837685526
MonotocityNot monotonic
2020-11-30T23:55:23.488418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
016127084.1%
 
6158938.3%
 
338562.0%
 
236431.9%
 
733081.7%
 
524391.3%
 
48230.4%
 
14200.2%
 
ValueCountFrequency (%) 
016127084.1%
 
14200.2%
 
236431.9%
 
338562.0%
 
48230.4%
 
524391.3%
 
6158938.3%
 
733081.7%
 
ValueCountFrequency (%) 
733081.7%
 
6158938.3%
 
524391.3%
 
48230.4%
 
338562.0%
 
236431.9%
 
14200.2%
 
016127084.1%
 

D19_REISEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.775556738
Minimum0
Maximum7
Zeros134825
Zeros (%)70.3%
Memory size1.5 MiB
2020-11-30T23:55:23.596191image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.80323014
Coefficient of variation (CV)1.57878939
Kurtosis-0.9166628182
Mean1.775556738
Median Absolute Deviation (MAD)0
Skewness1.001647035
Sum340289
Variance7.858099217
MonotocityNot monotonic
2020-11-30T23:55:23.702634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
013482570.3%
 
63424417.9%
 
7163978.6%
 
220781.1%
 
319821.0%
 
516530.9%
 
44020.2%
 
171< 0.1%
 
ValueCountFrequency (%) 
013482570.3%
 
171< 0.1%
 
220781.1%
 
319821.0%
 
44020.2%
 
516530.9%
 
63424417.9%
 
7163978.6%
 
ValueCountFrequency (%) 
7163978.6%
 
63424417.9%
 
516530.9%
 
44020.2%
 
319821.0%
 
220781.1%
 
171< 0.1%
 
013482570.3%
 

D19_SAMMELARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.432179158
Minimum0
Maximum7
Zeros145113
Zeros (%)75.7%
Memory size1.5 MiB
2020-11-30T23:55:23.813018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.551136246
Coefficient of variation (CV)1.781296866
Kurtosis-0.4070965951
Mean1.432179158
Median Absolute Deviation (MAD)0
Skewness1.245248736
Sum274480
Variance6.508296146
MonotocityNot monotonic
2020-11-30T23:55:23.911039image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
014511375.7%
 
63960520.7%
 
729581.5%
 
520691.1%
 
316070.8%
 
41970.1%
 
287< 0.1%
 
116< 0.1%
 
ValueCountFrequency (%) 
014511375.7%
 
116< 0.1%
 
287< 0.1%
 
316070.8%
 
41970.1%
 
520691.1%
 
63960520.7%
 
729581.5%
 
ValueCountFrequency (%) 
729581.5%
 
63960520.7%
 
520691.1%
 
41970.1%
 
316070.8%
 
287< 0.1%
 
116< 0.1%
 
014511375.7%
 

D19_SCHUHE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.598788429
Minimum0
Maximum7
Zeros163720
Zeros (%)85.4%
Memory size1.5 MiB
2020-11-30T23:55:24.016058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.584453772
Coefficient of variation (CV)2.646099515
Kurtosis5.714806054
Mean0.598788429
Median Absolute Deviation (MAD)0
Skewness2.629301269
Sum114759
Variance2.510493755
MonotocityNot monotonic
2020-11-30T23:55:24.116898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
016372085.4%
 
398565.1%
 
670423.7%
 
544852.3%
 
232551.7%
 
714250.7%
 
111490.6%
 
47200.4%
 
ValueCountFrequency (%) 
016372085.4%
 
111490.6%
 
232551.7%
 
398565.1%
 
47200.4%
 
544852.3%
 
670423.7%
 
714250.7%
 
ValueCountFrequency (%) 
714250.7%
 
670423.7%
 
544852.3%
 
47200.4%
 
398565.1%
 
232551.7%
 
111490.6%
 
016372085.4%
 

D19_SONSTIGE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.26943627
Minimum0
Maximum7
Zeros76573
Zeros (%)40.0%
Memory size1.5 MiB
2020-11-30T23:55:24.226612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.88042826
Coefficient of variation (CV)0.8810167938
Kurtosis-1.807866063
Mean3.26943627
Median Absolute Deviation (MAD)3
Skewness-0.09844980588
Sum626594
Variance8.296866961
MonotocityNot monotonic
2020-11-30T23:55:24.324314image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
07657340.0%
 
66781335.4%
 
7158358.3%
 
3140597.3%
 
595215.0%
 
235341.8%
 
425681.3%
 
117490.9%
 
ValueCountFrequency (%) 
07657340.0%
 
117490.9%
 
235341.8%
 
3140597.3%
 
425681.3%
 
595215.0%
 
66781335.4%
 
7158358.3%
 
ValueCountFrequency (%) 
7158358.3%
 
66781335.4%
 
595215.0%
 
425681.3%
 
3140597.3%
 
235341.8%
 
117490.9%
 
07657340.0%
 

D19_SOZIALES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Infinite0
Infinite (%)0.0%
Mean1.243590011
Minimum0
Maximum5
Zeros22750
Zeros (%)11.9%
Memory size1.5 MiB
2020-11-30T23:55:24.429410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.158866932
Coefficient of variation (CV)0.9318721779
Kurtosis3.602939994
Mean1.243590011
Median Absolute Deviation (MAD)0
Skewness1.984054596
Sum179021
Variance1.342972565
MonotocityNot monotonic
2020-11-30T23:55:24.531165image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
19896451.6%
 
02275011.9%
 
564053.3%
 
458613.1%
 
253372.8%
 
346382.4%
 
(Missing)4769724.9%
 
ValueCountFrequency (%) 
02275011.9%
 
19896451.6%
 
253372.8%
 
346382.4%
 
458613.1%
 
564053.3%
 
ValueCountFrequency (%) 
564053.3%
 
458613.1%
 
346382.4%
 
253372.8%
 
19896451.6%
 
02275011.9%
 

D19_TECHNIK
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.324233507
Minimum0
Maximum7
Zeros117416
Zeros (%)61.3%
Memory size1.5 MiB
2020-11-30T23:55:24.627536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.973774655
Coefficient of variation (CV)1.279464669
Kurtosis-1.633243217
Mean2.324233507
Median Absolute Deviation (MAD)0
Skewness0.5437674919
Sum445444
Variance8.843335698
MonotocityNot monotonic
2020-11-30T23:55:24.724824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
011741661.3%
 
65006626.1%
 
7161278.4%
 
540342.1%
 
333621.8%
 
43380.2%
 
22420.1%
 
167< 0.1%
 
ValueCountFrequency (%) 
011741661.3%
 
167< 0.1%
 
22420.1%
 
333621.8%
 
43380.2%
 
540342.1%
 
65006626.1%
 
7161278.4%
 
ValueCountFrequency (%) 
7161278.4%
 
65006626.1%
 
540342.1%
 
43380.2%
 
333621.8%
 
22420.1%
 
167< 0.1%
 
011741661.3%
 

D19_TELKO_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04522780874
Minimum0
Maximum6
Zeros184467
Zeros (%)96.3%
Memory size1.5 MiB
2020-11-30T23:55:24.828594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2466779489
Coefficient of variation (CV)5.454121165
Kurtosis56.35872517
Mean0.04522780874
Median Absolute Deviation (MAD)0
Skewness6.60333153
Sum8668
Variance0.06085001046
MonotocityNot monotonic
2020-11-30T23:55:24.925290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
018446796.3%
 
158503.1%
 
212310.6%
 
373< 0.1%
 
423< 0.1%
 
65< 0.1%
 
53< 0.1%
 
ValueCountFrequency (%) 
018446796.3%
 
158503.1%
 
212310.6%
 
373< 0.1%
 
423< 0.1%
 
53< 0.1%
 
65< 0.1%
 
ValueCountFrequency (%) 
65< 0.1%
 
53< 0.1%
 
423< 0.1%
 
373< 0.1%
 
212310.6%
 
158503.1%
 
018446796.3%
 

D19_TELKO_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08687099535
Minimum0
Maximum6
Zeros178411
Zeros (%)93.1%
Memory size1.5 MiB
2020-11-30T23:55:25.034007image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3464445385
Coefficient of variation (CV)3.988034639
Kurtosis27.34333128
Mean0.08687099535
Median Absolute Deviation (MAD)0
Skewness4.731110702
Sum16649
Variance0.1200238183
MonotocityNot monotonic
2020-11-30T23:55:25.118704image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
017841193.1%
 
1102145.3%
 
227361.4%
 
32170.1%
 
463< 0.1%
 
56< 0.1%
 
65< 0.1%
 
ValueCountFrequency (%) 
017841193.1%
 
1102145.3%
 
227361.4%
 
32170.1%
 
463< 0.1%
 
56< 0.1%
 
65< 0.1%
 
ValueCountFrequency (%) 
65< 0.1%
 
56< 0.1%
 
463< 0.1%
 
32170.1%
 
227361.4%
 
1102145.3%
 
017841193.1%
 

D19_TELKO_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.482014276
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:25.219263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.288102745
Coefficient of variation (CV)0.1358469528
Kurtosis11.87268648
Mean9.482014276
Median Absolute Deviation (MAD)0
Skewness-3.27854404
Sum1817247
Variance1.659208682
MonotocityNot monotonic
2020-11-30T23:55:25.320113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1014891577.7%
 
92149611.2%
 
880004.2%
 
550422.6%
 
731371.6%
 
629191.5%
 
48770.5%
 
14910.3%
 
34010.2%
 
23740.2%
 
ValueCountFrequency (%) 
14910.3%
 
23740.2%
 
34010.2%
 
48770.5%
 
550422.6%
 
629191.5%
 
731371.6%
 
880004.2%
 
92149611.2%
 
1014891577.7%
 
ValueCountFrequency (%) 
1014891577.7%
 
92149611.2%
 
880004.2%
 
731371.6%
 
629191.5%
 
550422.6%
 
48770.5%
 
34010.2%
 
23740.2%
 
14910.3%
 

D19_TELKO_MOBILE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.928693674
Minimum0
Maximum7
Zeros159544
Zeros (%)83.2%
Memory size1.5 MiB
2020-11-30T23:55:25.420471image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.124832386
Coefficient of variation (CV)2.287979821
Kurtosis1.867243737
Mean0.928693674
Median Absolute Deviation (MAD)0
Skewness1.931076588
Sum177986
Variance4.514912668
MonotocityNot monotonic
2020-11-30T23:55:25.525040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
015954483.2%
 
62223811.6%
 
337612.0%
 
526801.4%
 
724601.3%
 
44330.2%
 
23870.2%
 
11490.1%
 
ValueCountFrequency (%) 
015954483.2%
 
11490.1%
 
23870.2%
 
337612.0%
 
44330.2%
 
526801.4%
 
62223811.6%
 
724601.3%
 
ValueCountFrequency (%) 
724601.3%
 
62223811.6%
 
526801.4%
 
44330.2%
 
337612.0%
 
23870.2%
 
11490.1%
 
015954483.2%
 

D19_TELKO_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.799339428
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:25.636862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8326105321
Coefficient of variation (CV)0.08496598553
Kurtosis31.24514428
Mean9.799339428
Median Absolute Deviation (MAD)0
Skewness-5.284351942
Sum1878063
Variance0.6932402981
MonotocityNot monotonic
2020-11-30T23:55:25.733504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1017567591.7%
 
970413.7%
 
840442.1%
 
528801.5%
 
69480.5%
 
76060.3%
 
41920.1%
 
11160.1%
 
378< 0.1%
 
272< 0.1%
 
ValueCountFrequency (%) 
11160.1%
 
272< 0.1%
 
378< 0.1%
 
41920.1%
 
528801.5%
 
69480.5%
 
76060.3%
 
840442.1%
 
970413.7%
 
1017567591.7%
 
ValueCountFrequency (%) 
1017567591.7%
 
970413.7%
 
840442.1%
 
76060.3%
 
69480.5%
 
528801.5%
 
41920.1%
 
378< 0.1%
 
272< 0.1%
 
11160.1%
 

D19_TELKO_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.978001795
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:25.839331image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2602371818
Coefficient of variation (CV)0.0260810919
Kurtosis354.110959
Mean9.978001795
Median Absolute Deviation (MAD)0
Skewness-16.90329219
Sum1912304
Variance0.06772339079
MonotocityNot monotonic
2020-11-30T23:55:25.944162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1018951698.9%
 
911820.6%
 
84820.3%
 
71490.1%
 
51290.1%
 
61250.1%
 
436< 0.1%
 
213< 0.1%
 
311< 0.1%
 
19< 0.1%
 
ValueCountFrequency (%) 
19< 0.1%
 
213< 0.1%
 
311< 0.1%
 
436< 0.1%
 
51290.1%
 
61250.1%
 
71490.1%
 
84820.3%
 
911820.6%
 
1018951698.9%
 
ValueCountFrequency (%) 
1018951698.9%
 
911820.6%
 
84820.3%
 
71490.1%
 
61250.1%
 
51290.1%
 
436< 0.1%
 
311< 0.1%
 
213< 0.1%
 
19< 0.1%
 

D19_TELKO_ONLINE_QUOTE_12
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Memory size1.5 MiB
0
143757 
10
 
194
5
 
3
3
 
1
ValueCountFrequency (%) 
014375775.0%
 
101940.1%
 
53< 0.1%
 
31< 0.1%
 
(Missing)4769724.9%
 
2020-11-30T23:55:26.070641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
028790650.1%
 
.14395525.0%
 
n9539416.6%
 
a476978.3%
 
1194< 0.1%
 
53< 0.1%
 
31< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28810450.1%
 
Other Punctuation14395525.0%
 
Lowercase Letter14309124.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
028790699.9%
 
11940.1%
 
53< 0.1%
 
31< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.143955100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n9539466.7%
 
a4769733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common43205975.1%
 
Latin14309124.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
028790666.6%
 
.14395533.3%
 
1194< 0.1%
 
53< 0.1%
 
31< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n9539466.7%
 
a4769733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII575150100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
028790650.1%
 
.14395525.0%
 
n9539416.6%
 
a476978.3%
 
1194< 0.1%
 
53< 0.1%
 
31< 0.1%
 

D19_TELKO_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6513785403
Minimum0
Maximum7
Zeros168650
Zeros (%)88.0%
Memory size1.5 MiB
2020-11-30T23:55:26.174668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.811244014
Coefficient of variation (CV)2.780632002
Kurtosis4.579967189
Mean0.6513785403
Median Absolute Deviation (MAD)0
Skewness2.523157863
Sum124838
Variance3.28060488
MonotocityNot monotonic
2020-11-30T23:55:26.279375image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
016865088.0%
 
6142827.5%
 
532801.7%
 
331801.7%
 
716000.8%
 
43630.2%
 
22570.1%
 
140< 0.1%
 
ValueCountFrequency (%) 
016865088.0%
 
140< 0.1%
 
22570.1%
 
331801.7%
 
43630.2%
 
532801.7%
 
6142827.5%
 
716000.8%
 
ValueCountFrequency (%) 
716000.8%
 
6142827.5%
 
532801.7%
 
43630.2%
 
331801.7%
 
22570.1%
 
140< 0.1%
 
016865088.0%
 

D19_TIERARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2342474902
Minimum0
Maximum7
Zeros183788
Zeros (%)95.9%
Memory size1.5 MiB
2020-11-30T23:55:26.391666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.167000681
Coefficient of variation (CV)4.981913272
Kurtosis23.33408455
Mean0.2342474902
Median Absolute Deviation (MAD)0
Skewness4.969094841
Sum44894
Variance1.361890588
MonotocityNot monotonic
2020-11-30T23:55:26.490508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
018378895.9%
 
632661.7%
 
725241.3%
 
311360.6%
 
57370.4%
 
21290.1%
 
469< 0.1%
 
13< 0.1%
 
ValueCountFrequency (%) 
018378895.9%
 
13< 0.1%
 
21290.1%
 
311360.6%
 
469< 0.1%
 
57370.4%
 
632661.7%
 
725241.3%
 
ValueCountFrequency (%) 
725241.3%
 
632661.7%
 
57370.4%
 
469< 0.1%
 
311360.6%
 
21290.1%
 
13< 0.1%
 
018378895.9%
 

D19_VERSAND_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7712833678
Minimum0
Maximum6
Zeros122306
Zeros (%)63.8%
Memory size1.5 MiB
2020-11-30T23:55:26.595813image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.254807319
Coefficient of variation (CV)1.626908308
Kurtosis2.23676537
Mean0.7712833678
Median Absolute Deviation (MAD)0
Skewness1.705917564
Sum147818
Variance1.574541407
MonotocityNot monotonic
2020-11-30T23:55:26.683399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
012230663.8%
 
12671413.9%
 
22207611.5%
 
391324.8%
 
480854.2%
 
528181.5%
 
65210.3%
 
ValueCountFrequency (%) 
012230663.8%
 
12671413.9%
 
22207611.5%
 
391324.8%
 
480854.2%
 
528181.5%
 
65210.3%
 
ValueCountFrequency (%) 
65210.3%
 
528181.5%
 
480854.2%
 
391324.8%
 
22207611.5%
 
12671413.9%
 
012230663.8%
 

D19_VERSAND_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.206285351
Minimum0
Maximum6
Zeros102484
Zeros (%)53.5%
Memory size1.5 MiB
2020-11-30T23:55:26.780852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.622334458
Coefficient of variation (CV)1.344901069
Kurtosis0.3578673553
Mean1.206285351
Median Absolute Deviation (MAD)0
Skewness1.204625579
Sum231187
Variance2.631969093
MonotocityNot monotonic
2020-11-30T23:55:26.871548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
010248453.5%
 
22572313.4%
 
12497313.0%
 
4143537.5%
 
3130736.8%
 
581394.2%
 
629071.5%
 
ValueCountFrequency (%) 
010248453.5%
 
12497313.0%
 
22572313.4%
 
3130736.8%
 
4143537.5%
 
581394.2%
 
629071.5%
 
ValueCountFrequency (%) 
629071.5%
 
581394.2%
 
4143537.5%
 
3130736.8%
 
22572313.4%
 
12497313.0%
 
010248453.5%
 

D19_VERSAND_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.164167345
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:26.980371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.09421772
Coefficient of variation (CV)0.4319019323
Kurtosis-0.9017408821
Mean7.164167345
Median Absolute Deviation (MAD)1
Skewness-0.7122862189
Sum1373027
Variance9.574183296
MonotocityNot monotonic
2020-11-30T23:55:27.079281image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
107314238.2%
 
92345912.2%
 
52196811.5%
 
1142827.5%
 
8134907.0%
 
2110265.8%
 
6104015.4%
 
488204.6%
 
783764.4%
 
366883.5%
 
ValueCountFrequency (%) 
1142827.5%
 
2110265.8%
 
366883.5%
 
488204.6%
 
52196811.5%
 
6104015.4%
 
783764.4%
 
8134907.0%
 
92345912.2%
 
107314238.2%
 
ValueCountFrequency (%) 
107314238.2%
 
92345912.2%
 
8134907.0%
 
783764.4%
 
6104015.4%
 
52196811.5%
 
488204.6%
 
366883.5%
 
2110265.8%
 
1142827.5%
 

D19_VERSAND_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.691237243
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:27.173252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q18
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.987109535
Coefficient of variation (CV)0.2286336778
Kurtosis2.97058246
Mean8.691237243
Median Absolute Deviation (MAD)0
Skewness-1.842252112
Sum1665693
Variance3.948604306
MonotocityNot monotonic
2020-11-30T23:55:27.257400image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1010006152.2%
 
93657319.1%
 
82002210.4%
 
5121246.3%
 
777984.1%
 
664993.4%
 
226761.4%
 
422671.2%
 
118831.0%
 
317490.9%
 
ValueCountFrequency (%) 
118831.0%
 
226761.4%
 
317490.9%
 
422671.2%
 
5121246.3%
 
664993.4%
 
777984.1%
 
82002210.4%
 
93657319.1%
 
1010006152.2%
 
ValueCountFrequency (%) 
1010006152.2%
 
93657319.1%
 
82002210.4%
 
777984.1%
 
664993.4%
 
5121246.3%
 
422671.2%
 
317490.9%
 
226761.4%
 
118831.0%
 

D19_VERSAND_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.699783983
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:27.347092image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.033626886
Coefficient of variation (CV)0.3939885707
Kurtosis-0.4137265446
Mean7.699783983
Median Absolute Deviation (MAD)0
Skewness-1.016201771
Sum1475679
Variance9.202892085
MonotocityNot monotonic
2020-11-30T23:55:27.434490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
109760750.9%
 
9186699.7%
 
5165698.6%
 
1123106.4%
 
288304.6%
 
687934.6%
 
887824.6%
 
476154.0%
 
769673.6%
 
355102.9%
 
ValueCountFrequency (%) 
1123106.4%
 
288304.6%
 
355102.9%
 
476154.0%
 
5165698.6%
 
687934.6%
 
769673.6%
 
887824.6%
 
9186699.7%
 
109760750.9%
 
ValueCountFrequency (%) 
109760750.9%
 
9186699.7%
 
887824.6%
 
769673.6%
 
687934.6%
 
5165698.6%
 
476154.0%
 
355102.9%
 
288304.6%
 
1123106.4%
 

D19_VERSAND_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Infinite0
Infinite (%)0.0%
Mean3.216088361
Minimum0
Maximum10
Zeros92458
Zeros (%)48.2%
Memory size1.5 MiB
2020-11-30T23:55:27.523818image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q310
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)10

Descriptive statistics

Standard deviation4.486796355
Coefficient of variation (CV)1.395109789
Kurtosis-1.355994287
Mean3.216088361
Median Absolute Deviation (MAD)0
Skewness0.7516134975
Sum462972
Variance20.13134154
MonotocityNot monotonic
2020-11-30T23:55:27.614885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
09245848.2%
 
103919820.5%
 
535471.9%
 
821691.1%
 
720161.1%
 
315690.8%
 
912270.6%
 
65170.3%
 
24690.2%
 
44060.2%
 
13790.2%
 
(Missing)4769724.9%
 
ValueCountFrequency (%) 
09245848.2%
 
13790.2%
 
24690.2%
 
315690.8%
 
44060.2%
 
535471.9%
 
65170.3%
 
720161.1%
 
821691.1%
 
912270.6%
 
ValueCountFrequency (%) 
103919820.5%
 
912270.6%
 
821691.1%
 
720161.1%
 
65170.3%
 
535471.9%
 
44060.2%
 
315690.8%
 
24690.2%
 
13790.2%
 

D19_VERSAND_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7767672657
Minimum0
Maximum7
Zeros161199
Zeros (%)84.1%
Memory size1.5 MiB
2020-11-30T23:55:27.705689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.884115822
Coefficient of variation (CV)2.425586022
Kurtosis3.151972912
Mean0.7767672657
Median Absolute Deviation (MAD)0
Skewness2.193928047
Sum148869
Variance3.549892429
MonotocityNot monotonic
2020-11-30T23:55:27.796323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
016119984.1%
 
6141947.4%
 
375543.9%
 
548842.5%
 
716100.8%
 
29520.5%
 
47300.4%
 
15290.3%
 
ValueCountFrequency (%) 
016119984.1%
 
15290.3%
 
29520.5%
 
375543.9%
 
47300.4%
 
548842.5%
 
6141947.4%
 
716100.8%
 
ValueCountFrequency (%) 
716100.8%
 
6141947.4%
 
548842.5%
 
47300.4%
 
375543.9%
 
29520.5%
 
15290.3%
 
016119984.1%
 

D19_VERSI_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1017469163
Minimum0
Maximum6
Zeros177236
Zeros (%)92.5%
Memory size1.5 MiB
2020-11-30T23:55:27.894022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3933027945
Coefficient of variation (CV)3.865500881
Kurtosis24.98476259
Mean0.1017469163
Median Absolute Deviation (MAD)0
Skewness4.606203053
Sum19500
Variance0.1546870882
MonotocityNot monotonic
2020-11-30T23:55:27.979076image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
017723692.5%
 
1101355.3%
 
236391.9%
 
34960.3%
 
41330.1%
 
511< 0.1%
 
62< 0.1%
 
ValueCountFrequency (%) 
017723692.5%
 
1101355.3%
 
236391.9%
 
34960.3%
 
41330.1%
 
511< 0.1%
 
62< 0.1%
 
ValueCountFrequency (%) 
62< 0.1%
 
511< 0.1%
 
41330.1%
 
34960.3%
 
236391.9%
 
1101355.3%
 
017723692.5%
 

D19_VERSI_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1758865026
Minimum0
Maximum6
Zeros168832
Zeros (%)88.1%
Memory size1.5 MiB
2020-11-30T23:55:28.068627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5395389456
Coefficient of variation (CV)3.06754036
Kurtosis15.68757288
Mean0.1758865026
Median Absolute Deviation (MAD)0
Skewness3.678268234
Sum33709
Variance0.2911022738
MonotocityNot monotonic
2020-11-30T23:55:28.151811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
016883288.1%
 
1143427.5%
 
266913.5%
 
312360.6%
 
44860.3%
 
557< 0.1%
 
68< 0.1%
 
ValueCountFrequency (%) 
016883288.1%
 
1143427.5%
 
266913.5%
 
312360.6%
 
44860.3%
 
557< 0.1%
 
68< 0.1%
 
ValueCountFrequency (%) 
68< 0.1%
 
557< 0.1%
 
44860.3%
 
312360.6%
 
266913.5%
 
1143427.5%
 
016883288.1%
 

D19_VERSI_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.209170789
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:28.242950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.856679741
Coefficient of variation (CV)0.2016120435
Kurtosis6.730387969
Mean9.209170789
Median Absolute Deviation (MAD)0
Skewness-2.691987659
Sum1764956
Variance3.447259662
MonotocityNot monotonic
2020-11-30T23:55:28.324324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1014675876.6%
 
9152408.0%
 
868343.6%
 
564923.4%
 
647402.5%
 
736641.9%
 
231651.7%
 
417710.9%
 
116910.9%
 
312970.7%
 
ValueCountFrequency (%) 
116910.9%
 
231651.7%
 
312970.7%
 
417710.9%
 
564923.4%
 
647402.5%
 
736641.9%
 
868343.6%
 
9152408.0%
 
1014675876.6%
 
ValueCountFrequency (%) 
1014675876.6%
 
9152408.0%
 
868343.6%
 
736641.9%
 
647402.5%
 
564923.4%
 
417710.9%
 
312970.7%
 
231651.7%
 
116910.9%
 

D19_VERSI_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.917298019
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:28.414519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5634249934
Coefficient of variation (CV)0.05681234872
Kurtosis67.68284061
Mean9.917298019
Median Absolute Deviation (MAD)0
Skewness-7.986854681
Sum1900670
Variance0.3174477232
MonotocityNot monotonic
2020-11-30T23:55:28.502592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1018592897.0%
 
921361.1%
 
517230.9%
 
812160.6%
 
63650.2%
 
71970.1%
 
437< 0.1%
 
224< 0.1%
 
316< 0.1%
 
110< 0.1%
 
ValueCountFrequency (%) 
110< 0.1%
 
224< 0.1%
 
316< 0.1%
 
437< 0.1%
 
517230.9%
 
63650.2%
 
71970.1%
 
812160.6%
 
921361.1%
 
1018592897.0%
 
ValueCountFrequency (%) 
1018592897.0%
 
921361.1%
 
812160.6%
 
71970.1%
 
63650.2%
 
517230.9%
 
437< 0.1%
 
316< 0.1%
 
224< 0.1%
 
110< 0.1%
 

D19_VERSI_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.98316219
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:28.595652image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2613317165
Coefficient of variation (CV)0.02617724841
Kurtosis430.3124448
Mean9.98316219
Median Absolute Deviation (MAD)0
Skewness-19.37376118
Sum1913293
Variance0.06829426607
MonotocityNot monotonic
2020-11-30T23:55:28.680674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1019050999.4%
 
93940.2%
 
82120.1%
 
71720.1%
 
51650.1%
 
61070.1%
 
449< 0.1%
 
319< 0.1%
 
113< 0.1%
 
212< 0.1%
 
ValueCountFrequency (%) 
113< 0.1%
 
212< 0.1%
 
319< 0.1%
 
449< 0.1%
 
51650.1%
 
61070.1%
 
71720.1%
 
82120.1%
 
93940.2%
 
1019050999.4%
 
ValueCountFrequency (%) 
1019050999.4%
 
93940.2%
 
82120.1%
 
71720.1%
 
61070.1%
 
51650.1%
 
449< 0.1%
 
319< 0.1%
 
212< 0.1%
 
113< 0.1%
 

D19_VERSI_ONLINE_QUOTE_12
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing47697
Missing (%)24.9%
Memory size1.5 MiB
0
143697 
10
 
245
5
 
11
7
 
2
ValueCountFrequency (%) 
014369775.0%
 
102450.1%
 
511< 0.1%
 
72< 0.1%
 
(Missing)4769724.9%
 
2020-11-30T23:55:28.783282image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
028789750.1%
 
.14395525.0%
 
n9539416.6%
 
a476978.3%
 
1245< 0.1%
 
511< 0.1%
 
72< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28815550.1%
 
Other Punctuation14395525.0%
 
Lowercase Letter14309124.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
028789799.9%
 
12450.1%
 
511< 0.1%
 
72< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.143955100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n9539466.7%
 
a4769733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common43211075.1%
 
Latin14309124.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
028789766.6%
 
.14395533.3%
 
12450.1%
 
511< 0.1%
 
72< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n9539466.7%
 
a4769733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII575201100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
028789750.1%
 
.14395525.0%
 
n9539416.6%
 
a476978.3%
 
1245< 0.1%
 
511< 0.1%
 
72< 0.1%
 

D19_VERSICHERUNGEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.168612903
Minimum0
Maximum7
Zeros144720
Zeros (%)75.5%
Memory size1.5 MiB
2020-11-30T23:55:28.870503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.19925685
Coefficient of variation (CV)1.881937847
Kurtosis0.6245897634
Mean1.168612903
Median Absolute Deviation (MAD)0
Skewness1.533363389
Sum223967
Variance4.836730693
MonotocityNot monotonic
2020-11-30T23:55:28.954974image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
014472075.5%
 
62207411.5%
 
3101355.3%
 
562243.2%
 
227311.4%
 
421801.1%
 
720381.1%
 
115500.8%
 
ValueCountFrequency (%) 
014472075.5%
 
115500.8%
 
227311.4%
 
3101355.3%
 
421801.1%
 
562243.2%
 
62207411.5%
 
720381.1%
 
ValueCountFrequency (%) 
720381.1%
 
62207411.5%
 
562243.2%
 
421801.1%
 
3101355.3%
 
227311.4%
 
115500.8%
 
014472075.5%
 

D19_VOLLSORTIMENT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.365892347
Minimum0
Maximum7
Zeros108259
Zeros (%)56.5%
Memory size1.5 MiB
2020-11-30T23:55:29.050434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.841913651
Coefficient of variation (CV)1.201201591
Kurtosis-1.620472871
Mean2.365892347
Median Absolute Deviation (MAD)0
Skewness0.4846577738
Sum453428
Variance8.076473199
MonotocityNot monotonic
2020-11-30T23:55:29.136654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
010825956.5%
 
64947525.8%
 
3116226.1%
 
7104995.5%
 
576684.0%
 
220511.1%
 
412330.6%
 
18450.4%
 
ValueCountFrequency (%) 
010825956.5%
 
18450.4%
 
220511.1%
 
3116226.1%
 
412330.6%
 
576684.0%
 
64947525.8%
 
7104995.5%
 
ValueCountFrequency (%) 
7104995.5%
 
64947525.8%
 
576684.0%
 
412330.6%
 
3116226.1%
 
220511.1%
 
18450.4%
 
010825956.5%
 

D19_WEIN_FEINKOST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7881263958
Minimum0
Maximum7
Zeros166431
Zeros (%)86.8%
Memory size1.5 MiB
2020-11-30T23:55:29.222898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.065434151
Coefficient of variation (CV)2.620688969
Kurtosis3.500394388
Mean0.7881263958
Median Absolute Deviation (MAD)0
Skewness2.312607798
Sum151046
Variance4.266018233
MonotocityNot monotonic
2020-11-30T23:55:29.305861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
016643186.8%
 
6129746.8%
 
784084.4%
 
321071.1%
 
514250.7%
 
41500.1%
 
21430.1%
 
114< 0.1%
 
ValueCountFrequency (%) 
016643186.8%
 
114< 0.1%
 
21430.1%
 
321071.1%
 
41500.1%
 
514250.7%
 
6129746.8%
 
784084.4%
 
ValueCountFrequency (%) 
784084.4%
 
6129746.8%
 
514250.7%
 
41500.1%
 
321071.1%
 
21430.1%
 
114< 0.1%
 
016643186.8%
 

DSL_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Memory size1.5 MiB
1
138494 
0
 
3231
(Missing)
49927 
ValueCountFrequency (%) 
113849472.3%
 
032311.7%
 
(Missing)4992726.1%
 

EINGEFUEGT_AM
Categorical

HIGH CARDINALITY
MISSING

Distinct3034
Distinct (%)2.1%
Missing49927
Missing (%)26.1%
Memory size1.5 MiB
1992-02-10 00:00:00
64744 
1992-02-12 00:00:00
43686 
2003-11-18 00:00:00
 
1066
2005-12-16 00:00:00
 
808
1995-02-07 00:00:00
 
569
Other values (3029)
30852 
ValueCountFrequency (%) 
1992-02-10 00:00:006474433.8%
 
1992-02-12 00:00:004368622.8%
 
2003-11-18 00:00:0010660.6%
 
2005-12-16 00:00:008080.4%
 
1995-02-07 00:00:005690.3%
 
2004-04-14 00:00:004430.2%
 
2005-08-23 00:00:003910.2%
 
2005-04-15 00:00:003630.2%
 
1993-03-01 00:00:003570.2%
 
1995-10-10 00:00:003170.2%
 
2000-05-10 00:00:003150.2%
 
1992-02-21 00:00:003040.2%
 
1993-09-21 00:00:002940.2%
 
1993-10-21 00:00:002870.1%
 
1993-09-22 00:00:002310.1%
 
1995-07-19 00:00:002090.1%
 
2005-04-12 00:00:002000.1%
 
1993-11-03 00:00:001930.1%
 
1995-08-02 00:00:001890.1%
 
1996-01-26 00:00:001870.1%
 
1993-11-02 00:00:001810.1%
 
1995-08-15 00:00:001800.1%
 
1995-10-17 00:00:001790.1%
 
1993-09-23 00:00:001770.1%
 
1993-01-20 00:00:001660.1%
 
Other values (3009)2568913.4%
 
(Missing)4992726.1%
 
2020-11-30T23:55:29.438541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1029 ?
Unique (%)0.7%

Overview of Unicode Properties

Unique unicode characters15
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
0108417938.1%
 
229316710.3%
 
-28345010.0%
 
:28345010.0%
 
12726239.6%
 
92683139.4%
 
1417255.0%
 
n998543.5%
 
a499271.8%
 
3133670.5%
 
5132660.5%
 
6107740.4%
 
4102540.4%
 
7102120.4%
 
879950.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number198415069.8%
 
Dash Punctuation28345010.0%
 
Other Punctuation28345010.0%
 
Lowercase Letter1497815.3%
 
Space Separator1417255.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
0108417954.6%
 
229316714.8%
 
127262313.7%
 
926831313.5%
 
3133670.7%
 
5132660.7%
 
6107740.5%
 
4102540.5%
 
7102120.5%
 
879950.4%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-283450100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
141725100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
:283450100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n9985466.7%
 
a4992733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common269277594.7%
 
Latin1497815.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
0108417940.3%
 
229316710.9%
 
-28345010.5%
 
:28345010.5%
 
127262310.1%
 
926831310.0%
 
1417255.3%
 
3133670.5%
 
5132660.5%
 
6107740.4%
 
4102540.4%
 
7102120.4%
 
879950.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n9985466.7%
 
a4992733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2842556100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
0108417938.1%
 
229316710.3%
 
-28345010.0%
 
:28345010.0%
 
12726239.6%
 
92683139.4%
 
1417255.0%
 
n998543.5%
 
a499271.8%
 
3133670.5%
 
5132660.5%
 
6107740.4%
 
4102540.4%
 
7102120.4%
 
879950.3%
 

EINGEZOGENAM_HH_JAHR
Real number (ℝ≥0)

MISSING

Distinct33
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean1999.185053
Minimum1986
Maximum2018
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:29.552906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1986
5-th percentile1994
Q11994
median1997
Q32004
95-th percentile2012
Maximum2018
Range32
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.17809944
Coefficient of variation (CV)0.00309030894
Kurtosis-0.05160858788
Mean1999.185053
Median Absolute Deviation (MAD)3
Skewness1.019184149
Sum289993787
Variance38.1689127
MonotocityNot monotonic
2020-11-30T23:55:29.652894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%) 
19945955931.1%
 
1997167868.8%
 
200490284.7%
 
200150892.7%
 
199949202.6%
 
200049112.6%
 
199847172.5%
 
200246822.4%
 
200740742.1%
 
200831271.6%
 
200326631.4%
 
200525831.3%
 
201525491.3%
 
201223131.2%
 
201422811.2%
 
200922751.2%
 
201122631.2%
 
200622401.2%
 
199620091.0%
 
201018801.0%
 
201317390.9%
 
199517310.9%
 
19934580.2%
 
20163360.2%
 
19923200.2%
 
Other values (8)5230.3%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
19867< 0.1%
 
198717< 0.1%
 
198834< 0.1%
 
198984< 0.1%
 
19901240.1%
 
19911450.1%
 
19923200.2%
 
19934580.2%
 
19945955931.1%
 
199517310.9%
 
ValueCountFrequency (%) 
201883< 0.1%
 
201729< 0.1%
 
20163360.2%
 
201525491.3%
 
201422811.2%
 
201317390.9%
 
201223131.2%
 
201122631.2%
 
201018801.0%
 
200922751.2%
 

EWDICHTE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing49959
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean3.88170199
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:29.746782image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.607620711
Coefficient of variation (CV)0.4141535633
Kurtosis-1.150113125
Mean3.88170199
Median Absolute Deviation (MAD)1
Skewness-0.2725504899
Sum550010
Variance2.584444349
MonotocityNot monotonic
2020-11-30T23:55:29.829985image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
53247516.9%
 
62736314.3%
 
42717014.2%
 
22554613.3%
 
3172739.0%
 
1118666.2%
 
(Missing)4995926.1%
 
ValueCountFrequency (%) 
1118666.2%
 
22554613.3%
 
3172739.0%
 
42717014.2%
 
53247516.9%
 
62736314.3%
 
ValueCountFrequency (%) 
62736314.3%
 
53247516.9%
 
42717014.2%
 
3172739.0%
 
22554613.3%
 
1118666.2%
 

EXTSEL992
Real number (ℝ≥0)

MISSING

Distinct56
Distinct (%)0.1%
Missing85283
Missing (%)44.5%
Infinite0
Infinite (%)0.0%
Mean38.4185994
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:29.934982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15
Q129
median36
Q353
95-th percentile56
Maximum56
Range55
Interquartile range (IQR)24

Descriptive statistics

Standard deviation13.68946562
Coefficient of variation (CV)0.3563239116
Kurtosis-0.4832495904
Mean38.4185994
Median Absolute Deviation (MAD)11
Skewness-0.4013270401
Sum4086548
Variance187.4014689
MonotocityNot monotonic
2020-11-30T23:55:30.051611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
56136567.1%
 
5573243.8%
 
3664363.4%
 
3162993.3%
 
2359913.1%
 
3555462.9%
 
3451472.7%
 
5044342.3%
 
2742072.2%
 
5333731.8%
 
5432791.7%
 
2631331.6%
 
4124541.3%
 
3824371.3%
 
4822711.2%
 
3721631.1%
 
4619381.0%
 
3919221.0%
 
4317230.9%
 
4016980.9%
 
3316160.8%
 
2915000.8%
 
4712110.6%
 
5210820.6%
 
2110700.6%
 
Other values (31)144597.5%
 
(Missing)8528344.5%
 
ValueCountFrequency (%) 
12530.1%
 
25170.3%
 
38470.4%
 
42920.2%
 
52670.1%
 
69900.5%
 
71100.1%
 
81230.1%
 
91830.1%
 
103340.2%
 
ValueCountFrequency (%) 
56136567.1%
 
5573243.8%
 
5432791.7%
 
5333731.8%
 
5210820.6%
 
513520.2%
 
5044342.3%
 
491000.1%
 
4822711.2%
 
4712110.6%
 

FINANZ_ANLEGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.439807568
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:30.154880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.697931919
Coefficient of variation (CV)0.695928622
Kurtosis-1.361260836
Mean2.439807568
Median Absolute Deviation (MAD)1
Skewness0.6284398669
Sum467594
Variance2.8829728
MonotocityNot monotonic
2020-11-30T23:55:30.234493image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
19443749.3%
 
55021626.2%
 
22648813.8%
 
3129436.8%
 
475683.9%
 
ValueCountFrequency (%) 
19443749.3%
 
22648813.8%
 
3129436.8%
 
475683.9%
 
55021626.2%
 
ValueCountFrequency (%) 
55021626.2%
 
475683.9%
 
3129436.8%
 
22648813.8%
 
19443749.3%
 

FINANZ_HAUSBAUER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.781176299
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:30.321747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.147352936
Coefficient of variation (CV)0.4125423247
Kurtosis-0.4444650242
Mean2.781176299
Median Absolute Deviation (MAD)1
Skewness0.3645580991
Sum533018
Variance1.316418759
MonotocityNot monotonic
2020-11-30T23:55:30.405485image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
37213937.6%
 
25370528.0%
 
12534013.2%
 
52197911.5%
 
4184899.6%
 
ValueCountFrequency (%) 
12534013.2%
 
25370528.0%
 
37213937.6%
 
4184899.6%
 
52197911.5%
 
ValueCountFrequency (%) 
52197911.5%
 
4184899.6%
 
37213937.6%
 
25370528.0%
 
12534013.2%
 

FINANZ_MINIMALIST
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.96377288
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:30.497211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.036229698
Coefficient of variation (CV)0.2614250941
Kurtosis-1.026101537
Mean3.96377288
Median Absolute Deviation (MAD)1
Skewness-0.4017127499
Sum759665
Variance1.073771987
MonotocityNot monotonic
2020-11-30T23:55:30.582430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
58444944.1%
 
36643934.7%
 
42916215.2%
 
298535.1%
 
117490.9%
 
ValueCountFrequency (%) 
117490.9%
 
298535.1%
 
36643934.7%
 
42916215.2%
 
58444944.1%
 
ValueCountFrequency (%) 
58444944.1%
 
42916215.2%
 
36643934.7%
 
298535.1%
 
117490.9%
 

FINANZ_SPARER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.057051322
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:30.674957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.31942176
Coefficient of variation (CV)0.6414141181
Kurtosis-1.270882913
Mean2.057051322
Median Absolute Deviation (MAD)0
Skewness0.6901530191
Sum394238
Variance1.74087378
MonotocityNot monotonic
2020-11-30T23:55:30.756760image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
110524054.9%
 
45069226.5%
 
22475212.9%
 
390574.7%
 
519111.0%
 
ValueCountFrequency (%) 
110524054.9%
 
22475212.9%
 
390574.7%
 
45069226.5%
 
519111.0%
 
ValueCountFrequency (%) 
519111.0%
 
45069226.5%
 
390574.7%
 
22475212.9%
 
110524054.9%
 

FINANZ_UNAUFFAELLIGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.646176403
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:30.844827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.586506089
Coefficient of variation (CV)0.599546609
Kurtosis-1.31626117
Mean2.646176403
Median Absolute Deviation (MAD)1
Skewness0.5109352912
Sum507145
Variance2.517001571
MonotocityNot monotonic
2020-11-30T23:55:30.929516image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
16138732.0%
 
25183027.0%
 
55110426.7%
 
32274611.9%
 
445852.4%
 
ValueCountFrequency (%) 
16138732.0%
 
25183027.0%
 
32274611.9%
 
445852.4%
 
55110426.7%
 
ValueCountFrequency (%) 
55110426.7%
 
445852.4%
 
32274611.9%
 
25183027.0%
 
16138732.0%
 

FINANZ_VORSORGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.183316636
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:31.021855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9953650632
Coefficient of variation (CV)0.2379368214
Kurtosis-0.309472941
Mean4.183316636
Median Absolute Deviation (MAD)0
Skewness-0.8217365764
Sum801741
Variance0.990751609
MonotocityNot monotonic
2020-11-30T23:55:31.102554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
510428654.4%
 
35437028.4%
 
42695414.1%
 
233431.7%
 
126991.4%
 
ValueCountFrequency (%) 
126991.4%
 
233431.7%
 
35437028.4%
 
42695414.1%
 
510428654.4%
 
ValueCountFrequency (%) 
510428654.4%
 
42695414.1%
 
35437028.4%
 
233431.7%
 
126991.4%
 

FINANZTYP
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.137958383
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:31.186312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median4
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.503945795
Coefficient of variation (CV)0.3634511649
Kurtosis-1.093061913
Mean4.137958383
Median Absolute Deviation (MAD)1
Skewness-0.3987347994
Sum793048
Variance2.261852953
MonotocityNot monotonic
2020-11-30T23:55:31.274672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
44844225.3%
 
54679224.4%
 
24427723.1%
 
64283122.3%
 
352352.7%
 
140752.1%
 
ValueCountFrequency (%) 
140752.1%
 
24427723.1%
 
352352.7%
 
44844225.3%
 
54679224.4%
 
64283122.3%
 
ValueCountFrequency (%) 
64283122.3%
 
54679224.4%
 
44844225.3%
 
352352.7%
 
24427723.1%
 
140752.1%
 

FIRMENDICHTE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean3.58001764
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:31.355515image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.051071624
Coefficient of variation (CV)0.2935939791
Kurtosis-0.4752324578
Mean3.58001764
Median Absolute Deviation (MAD)1
Skewness-0.4522959686
Sum507378
Variance1.104751559
MonotocityNot monotonic
2020-11-30T23:55:31.437699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
45400828.2%
 
33543818.5%
 
52828214.8%
 
21962510.2%
 
143722.3%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
143722.3%
 
21962510.2%
 
33543818.5%
 
45400828.2%
 
52828214.8%
 
ValueCountFrequency (%) 
52828214.8%
 
45400828.2%
 
33543818.5%
 
21962510.2%
 
143722.3%
 

GEBAEUDETYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean2.369941789
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:31.530581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.434226862
Coefficient of variation (CV)1.02712517
Kurtosis1.207693379
Mean2.369941789
Median Absolute Deviation (MAD)0
Skewness1.674515617
Sum335880
Variance5.925460416
MonotocityNot monotonic
2020-11-30T23:55:31.613822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
19514549.6%
 
32365512.3%
 
82047510.7%
 
220571.1%
 
42510.1%
 
61420.1%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
19514549.6%
 
220571.1%
 
32365512.3%
 
42510.1%
 
61420.1%
 
82047510.7%
 
ValueCountFrequency (%) 
82047510.7%
 
61420.1%
 
42510.1%
 
32365512.3%
 
220571.1%
 
19514549.6%
 

GEBAEUDETYP_RASTER
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean3.852524255
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:31.701843image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8302845101
Coefficient of variation (CV)0.2155170105
Kurtosis0.7751092996
Mean3.852524255
Median Absolute Deviation (MAD)0
Skewness-0.7050827219
Sum545999
Variance0.6893723678
MonotocityNot monotonic
2020-11-30T23:55:31.786921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
47424938.7%
 
33087516.1%
 
52828214.8%
 
266493.5%
 
116700.9%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
116700.9%
 
266493.5%
 
33087516.1%
 
47424938.7%
 
52828214.8%
 
ValueCountFrequency (%) 
52828214.8%
 
47424938.7%
 
33087516.1%
 
266493.5%
 
116700.9%
 

GEBURTSJAHR
Real number (ℝ≥0)

ZEROS

Distinct113
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1003.392733
Minimum0
Maximum2017
Zeros93024
Zeros (%)48.5%
Memory size1.5 MiB
2020-11-30T23:55:31.900923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1926
Q31949
95-th percentile1970
Maximum2017
Range2017
Interquartile range (IQR)1949

Descriptive statistics

Standard deviation974.5310809
Coefficient of variation (CV)0.971235937
Kurtosis-1.996152602
Mean1003.392733
Median Absolute Deviation (MAD)54
Skewness-0.05814304244
Sum192302224
Variance949710.8276
MonotocityNot monotonic
2020-11-30T23:55:32.024059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
09302448.5%
 
194135351.8%
 
194030851.6%
 
193930711.6%
 
194328751.5%
 
194228021.5%
 
193827751.4%
 
194426251.4%
 
193726031.4%
 
193624431.3%
 
194923521.2%
 
194822661.2%
 
195022301.2%
 
193522201.2%
 
194621651.1%
 
195421321.1%
 
194721301.1%
 
195121161.1%
 
195220911.1%
 
195320411.1%
 
195919621.0%
 
195519541.0%
 
193419321.0%
 
195619041.0%
 
196218921.0%
 
Other values (88)4142721.6%
 
ValueCountFrequency (%) 
09302448.5%
 
19003< 0.1%
 
19021< 0.1%
 
19081< 0.1%
 
19091< 0.1%
 
19106< 0.1%
 
191110< 0.1%
 
19127< 0.1%
 
19137< 0.1%
 
191413< 0.1%
 
ValueCountFrequency (%) 
201745< 0.1%
 
20167< 0.1%
 
201550< 0.1%
 
201419< 0.1%
 
201339< 0.1%
 
201268< 0.1%
 
20114< 0.1%
 
20102< 0.1%
 
20092< 0.1%
 
20086< 0.1%
 

GEMEINDETYP
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing50476
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean24.77668301
Minimum11
Maximum50
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:32.128664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q112
median22
Q330
95-th percentile50
Maximum50
Range39
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.75850998
Coefficient of variation (CV)0.4745796675
Kurtosis-0.6734788608
Mean24.77668301
Median Absolute Deviation (MAD)10
Skewness0.5624746734
Sum3497873
Variance138.262557
MonotocityNot monotonic
2020-11-30T23:55:32.227583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
222980815.6%
 
302474812.9%
 
122249411.7%
 
402173611.3%
 
111999210.4%
 
21130876.8%
 
5093114.9%
 
(Missing)5047626.3%
 
ValueCountFrequency (%) 
111999210.4%
 
122249411.7%
 
21130876.8%
 
222980815.6%
 
302474812.9%
 
402173611.3%
 
5093114.9%
 
ValueCountFrequency (%) 
5093114.9%
 
402173611.3%
 
302474812.9%
 
222980815.6%
 
21130876.8%
 
122249411.7%
 
111999210.4%
 

GFK_URLAUBERTYP
Real number (ℝ≥0)

MISSING

Distinct12
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean6.302267577
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:32.318488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median5
Q39
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.877181228
Coefficient of variation (CV)0.4565311124
Kurtosis-0.8363825052
Mean6.302267577
Median Absolute Deviation (MAD)2
Skewness0.2531100866
Sum1187593
Variance8.278171818
MonotocityNot monotonic
2020-11-30T23:55:32.402176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
55811330.3%
 
102729114.2%
 
8176319.2%
 
4163618.5%
 
3146847.7%
 
7138267.2%
 
187824.6%
 
1174863.9%
 
1273033.8%
 
663733.3%
 
955162.9%
 
250732.6%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
187824.6%
 
250732.6%
 
3146847.7%
 
4163618.5%
 
55811330.3%
 
663733.3%
 
7138267.2%
 
8176319.2%
 
955162.9%
 
102729114.2%
 
ValueCountFrequency (%) 
1273033.8%
 
1174863.9%
 
102729114.2%
 
955162.9%
 
8176319.2%
 
7138267.2%
 
663733.3%
 
55811330.3%
 
4163618.5%
 
3146847.7%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
0
121283 
1
70369 
ValueCountFrequency (%) 
012128363.3%
 
17036936.7%
 

HEALTH_TYP
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
2
56955 
-1
48990 
1
46183 
3
39524 
ValueCountFrequency (%) 
25695529.7%
 
-14899025.6%
 
14618324.1%
 
33952420.6%
 
2020-11-30T23:55:32.502140image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
19517339.5%
 
25695523.7%
 
-4899020.4%
 
33952416.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number19165279.6%
 
Dash Punctuation4899020.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
19517349.7%
 
25695529.7%
 
33952420.6%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-48990100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common240642100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
19517339.5%
 
25695523.7%
 
-4899020.4%
 
33952416.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII240642100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
19517339.5%
 
25695523.7%
 
-4899020.4%
 
33952416.4%
 

HH_DELTA_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing53742
Missing (%)28.0%
Memory size1.5 MiB
0
117263 
1
20647 
(Missing)
53742 
ValueCountFrequency (%) 
011726361.2%
 
12064710.8%
 
(Missing)5374228.0%
 

HH_EINKOMMEN_SCORE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing2968
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean2.942480549
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:32.585936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.533347234
Coefficient of variation (CV)0.5211070077
Kurtosis-0.8746764077
Mean2.942480549
Median Absolute Deviation (MAD)1
Skewness0.5570660097
Sum555199
Variance2.351153741
MonotocityNot monotonic
2020-11-30T23:55:32.672430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
27016036.6%
 
12993615.6%
 
42767414.4%
 
52392312.5%
 
32243811.7%
 
6145537.6%
 
(Missing)29681.5%
 
ValueCountFrequency (%) 
12993615.6%
 
27016036.6%
 
32243811.7%
 
42767414.4%
 
52392312.5%
 
6145537.6%
 
ValueCountFrequency (%) 
6145537.6%
 
52392312.5%
 
42767414.4%
 
32243811.7%
 
27016036.6%
 
12993615.6%
 

INNENSTADT
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing49959
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean4.784576514
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:32.757701image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q36
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.96147294
Coefficient of variation (CV)0.409957482
Kurtosis-0.8055497713
Mean4.784576514
Median Absolute Deviation (MAD)1
Skewness0.005190446354
Sum677941
Variance3.847376094
MonotocityNot monotonic
2020-11-30T23:55:32.836969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
52803114.6%
 
42770014.5%
 
61953210.2%
 
8180759.4%
 
3157928.2%
 
2143717.5%
 
7118146.2%
 
163783.3%
 
(Missing)4995926.1%
 
ValueCountFrequency (%) 
163783.3%
 
2143717.5%
 
3157928.2%
 
42770014.5%
 
52803114.6%
 
61953210.2%
 
7118146.2%
 
8180759.4%
 
ValueCountFrequency (%) 
8180759.4%
 
7118146.2%
 
61953210.2%
 
52803114.6%
 
42770014.5%
 
3157928.2%
 
2143717.5%
 
163783.3%
 

KBA05_ALTER1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.592075004
Minimum0
Maximum9
Zeros22932
Zeros (%)12.0%
Memory size1.5 MiB
2020-11-30T23:55:32.925950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.201312382
Coefficient of variation (CV)0.7545576553
Kurtosis8.267882678
Mean1.592075004
Median Absolute Deviation (MAD)1
Skewness1.678464283
Sum216000
Variance1.44315144
MonotocityNot monotonic
2020-11-30T23:55:33.003274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
14423223.1%
 
24359022.7%
 
02293212.0%
 
31974910.3%
 
442362.2%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
02293212.0%
 
14423223.1%
 
24359022.7%
 
31974910.3%
 
442362.2%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
442362.2%
 
31974910.3%
 
24359022.7%
 
14423223.1%
 
02293212.0%
 

KBA05_ALTER2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.797548499
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:33.083487image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.138182474
Coefficient of variation (CV)0.4068499524
Kurtosis4.736317378
Mean2.797548499
Median Absolute Deviation (MAD)1
Skewness1.144628188
Sum379549
Variance1.295459344
MonotocityNot monotonic
2020-11-30T23:55:33.162844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35263827.5%
 
23875120.2%
 
42147411.2%
 
1148857.8%
 
569913.6%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1148857.8%
 
23875120.2%
 
35263827.5%
 
42147411.2%
 
569913.6%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
569913.6%
 
42147411.2%
 
35263827.5%
 
23875120.2%
 
1148857.8%
 

KBA05_ALTER3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.170506811
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:33.249485image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.144634922
Coefficient of variation (CV)0.3610258518
Kurtosis3.380510694
Mean3.170506811
Median Absolute Deviation (MAD)1
Skewness0.79725924
Sum430149
Variance1.310189104
MonotocityNot monotonic
2020-11-30T23:55:33.328783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35422728.3%
 
43196616.7%
 
22601313.6%
 
5141627.4%
 
183714.4%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
183714.4%
 
22601313.6%
 
35422728.3%
 
43196616.7%
 
5141627.4%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5141627.4%
 
43196616.7%
 
35422728.3%
 
22601313.6%
 
183714.4%
 

KBA05_ALTER4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.315606757
Minimum0
Maximum9
Zeros2435
Zeros (%)1.3%
Memory size1.5 MiB
2020-11-30T23:55:33.417549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.197247528
Coefficient of variation (CV)0.3610945493
Kurtosis2.936314364
Mean3.315606757
Median Absolute Deviation (MAD)1
Skewness0.2757794943
Sum449835
Variance1.433401643
MonotocityNot monotonic
2020-11-30T23:55:33.496468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
35343927.9%
 
43737719.5%
 
5182949.5%
 
2169498.8%
 
162453.3%
 
024351.3%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
024351.3%
 
162453.3%
 
2169498.8%
 
35343927.9%
 
43737719.5%
 
5182949.5%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5182949.5%
 
43737719.5%
 
35343927.9%
 
2169498.8%
 
162453.3%
 
024351.3%
 

KBA05_ANHANG
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.164794504
Minimum0
Maximum9
Zeros36170
Zeros (%)18.9%
Memory size1.5 MiB
2020-11-30T23:55:33.576758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.138406712
Coefficient of variation (CV)0.9773455385
Kurtosis12.62911307
Mean1.164794504
Median Absolute Deviation (MAD)1
Skewness2.40768574
Sum158030
Variance1.295969842
MonotocityNot monotonic
2020-11-30T23:55:33.649085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
16508934.0%
 
03617018.9%
 
3180189.4%
 
2155248.1%
 
98710.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
03617018.9%
 
16508934.0%
 
2155248.1%
 
3180189.4%
 
98710.5%
 
ValueCountFrequency (%) 
98710.5%
 
3180189.4%
 
2155248.1%
 
16508934.0%
 
03617018.9%
 

KBA05_ANTG1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.207058199
Minimum0
Maximum4
Zeros22465
Zeros (%)11.7%
Memory size1.5 MiB
2020-11-30T23:55:33.726604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.38350859
Coefficient of variation (CV)0.626856415
Kurtosis-1.179724037
Mean2.207058199
Median Absolute Deviation (MAD)1
Skewness-0.2415022388
Sum299436
Variance1.91409602
MonotocityNot monotonic
2020-11-30T23:55:33.808701image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
33310917.3%
 
43040815.9%
 
22878715.0%
 
02246511.7%
 
12090310.9%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
02246511.7%
 
12090310.9%
 
22878715.0%
 
33310917.3%
 
43040815.9%
 
ValueCountFrequency (%) 
43040815.9%
 
33310917.3%
 
22878715.0%
 
12090310.9%
 
02246511.7%
 

KBA05_ANTG2
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.209004069
Minimum0
Maximum4
Zeros43729
Zeros (%)22.8%
Memory size1.5 MiB
2020-11-30T23:55:33.897801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum4
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.086202392
Coefficient of variation (CV)0.8984274083
Kurtosis-0.6215466687
Mean1.209004069
Median Absolute Deviation (MAD)1
Skewness0.5436267087
Sum164028
Variance1.179835636
MonotocityNot monotonic
2020-11-30T23:55:33.980338image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
04372922.8%
 
14207922.0%
 
23051315.9%
 
3164818.6%
 
428701.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
04372922.8%
 
14207922.0%
 
23051315.9%
 
3164818.6%
 
428701.5%
 
ValueCountFrequency (%) 
428701.5%
 
3164818.6%
 
23051315.9%
 
14207922.0%
 
04372922.8%
 

KBA05_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Memory size1.5 MiB
0
112655 
1
 
10163
2
 
6671
3
 
6183
ValueCountFrequency (%) 
011265558.8%
 
1101635.3%
 
266713.5%
 
361833.2%
 
(Missing)5598029.2%
 
2020-11-30T23:55:34.077295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
024832743.2%
 
.13567223.6%
 
n11196019.5%
 
a559809.7%
 
1101631.8%
 
266711.2%
 
361831.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27134447.2%
 
Lowercase Letter16794029.2%
 
Other Punctuation13567223.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
024832791.5%
 
1101633.7%
 
266712.5%
 
361832.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.135672100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common40701670.8%
 
Latin16794029.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
024832761.0%
 
.13567233.3%
 
1101632.5%
 
266711.6%
 
361831.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
024832743.2%
 
.13567223.6%
 
n11196019.5%
 
a559809.7%
 
1101631.8%
 
266711.2%
 
361831.1%
 

KBA05_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Memory size1.5 MiB
0
121487 
1
 
7560
2
 
6625
ValueCountFrequency (%) 
012148763.4%
 
175603.9%
 
266253.5%
 
(Missing)5598029.2%
 
2020-11-30T23:55:34.172967image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
025715944.7%
 
.13567223.6%
 
n11196019.5%
 
a559809.7%
 
175601.3%
 
266251.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27134447.2%
 
Lowercase Letter16794029.2%
 
Other Punctuation13567223.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
025715994.8%
 
175602.8%
 
266252.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.135672100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common40701670.8%
 
Latin16794029.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
025715963.2%
 
.13567233.3%
 
175601.9%
 
266251.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
025715944.7%
 
.13567223.6%
 
n11196019.5%
 
a559809.7%
 
175601.3%
 
266251.2%
 

KBA05_AUTOQUOT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.585139159
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:34.259124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.081234251
Coefficient of variation (CV)0.3015878054
Kurtosis3.504972143
Mean3.585139159
Median Absolute Deviation (MAD)1
Skewness0.3952850565
Sum486403
Variance1.169067506
MonotocityNot monotonic
2020-11-30T23:55:34.338415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
45219327.2%
 
34446023.2%
 
52168211.3%
 
2110325.8%
 
153712.8%
 
99340.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
153712.8%
 
2110325.8%
 
34446023.2%
 
45219327.2%
 
52168211.3%
 
99340.5%
 
ValueCountFrequency (%) 
99340.5%
 
52168211.3%
 
45219327.2%
 
34446023.2%
 
2110325.8%
 
153712.8%
 

KBA05_BAUMAX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.043826287
Minimum0
Maximum5
Zeros53555
Zeros (%)27.9%
Memory size1.5 MiB
2020-11-30T23:55:34.423487image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.384973137
Coefficient of variation (CV)1.326823395
Kurtosis2.626944134
Mean1.043826287
Median Absolute Deviation (MAD)1
Skewness1.863135698
Sum141618
Variance1.918150591
MonotocityNot monotonic
2020-11-30T23:55:34.506425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
16340833.1%
 
05355527.9%
 
599815.2%
 
348772.5%
 
429861.6%
 
28650.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
05355527.9%
 
16340833.1%
 
28650.5%
 
348772.5%
 
429861.6%
 
599815.2%
 
ValueCountFrequency (%) 
599815.2%
 
429861.6%
 
348772.5%
 
28650.5%
 
16340833.1%
 
05355527.9%
 

KBA05_CCM1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.812923816
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:34.587079image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.098849925
Coefficient of variation (CV)0.3906433294
Kurtosis5.601212496
Mean2.812923816
Median Absolute Deviation (MAD)1
Skewness1.227273526
Sum381635
Variance1.207471157
MonotocityNot monotonic
2020-11-30T23:55:34.665744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35636429.4%
 
23816719.9%
 
42134011.1%
 
1129726.8%
 
558963.1%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1129726.8%
 
23816719.9%
 
35636429.4%
 
42134011.1%
 
558963.1%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
558963.1%
 
42134011.1%
 
35636429.4%
 
23816719.9%
 
1129726.8%
 

KBA05_CCM2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.940783655
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:34.752770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.086483205
Coefficient of variation (CV)0.3694536328
Kurtosis5.377674774
Mean2.940783655
Median Absolute Deviation (MAD)1
Skewness1.121395826
Sum398982
Variance1.180445754
MonotocityNot monotonic
2020-11-30T23:55:34.832916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35887330.7%
 
23267817.1%
 
42613013.6%
 
1103005.4%
 
567583.5%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1103005.4%
 
23267817.1%
 
35887330.7%
 
42613013.6%
 
567583.5%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
567583.5%
 
42613013.6%
 
35887330.7%
 
23267817.1%
 
1103005.4%
 

KBA05_CCM3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.276630403
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:34.923731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.081889258
Coefficient of variation (CV)0.3301834887
Kurtosis4.201918951
Mean3.276630403
Median Absolute Deviation (MAD)1
Skewness0.8656901725
Sum444547
Variance1.170484366
MonotocityNot monotonic
2020-11-30T23:55:35.004876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35717329.8%
 
43675719.2%
 
22146611.2%
 
5138327.2%
 
155112.9%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
155112.9%
 
22146611.2%
 
35717329.8%
 
43675719.2%
 
5138327.2%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5138327.2%
 
43675719.2%
 
35717329.8%
 
22146611.2%
 
155112.9%
 

KBA05_CCM4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.544423315
Minimum0
Maximum9
Zeros32427
Zeros (%)16.9%
Memory size1.5 MiB
2020-11-30T23:55:35.094142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.374065005
Coefficient of variation (CV)0.889694549
Kurtosis4.387002818
Mean1.544423315
Median Absolute Deviation (MAD)1
Skewness1.389649065
Sum209535
Variance1.888054637
MonotocityNot monotonic
2020-11-30T23:55:35.171702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
14467523.3%
 
03242716.9%
 
22796014.6%
 
3181659.5%
 
4115126.0%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
03242716.9%
 
14467523.3%
 
22796014.6%
 
3181659.5%
 
4115126.0%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
4115126.0%
 
3181659.5%
 
22796014.6%
 
14467523.3%
 
03242716.9%
 

KBA05_DIESEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.229420956
Minimum0
Maximum9
Zeros5076
Zeros (%)2.6%
Memory size1.5 MiB
2020-11-30T23:55:35.255807image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.109139093
Coefficient of variation (CV)0.4975009719
Kurtosis8.074574473
Mean2.229420956
Median Absolute Deviation (MAD)1
Skewness1.461198503
Sum302470
Variance1.230189527
MonotocityNot monotonic
2020-11-30T23:55:35.330055image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
25806230.3%
 
33496418.2%
 
12449712.8%
 
4121406.3%
 
050762.6%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
050762.6%
 
12449712.8%
 
25806230.3%
 
33496418.2%
 
4121406.3%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
4121406.3%
 
33496418.2%
 
25806230.3%
 
12449712.8%
 
050762.6%
 

KBA05_FRAU
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.097639896
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:35.409285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.100045746
Coefficient of variation (CV)0.3551238306
Kurtosis4.498935757
Mean3.097639896
Median Absolute Deviation (MAD)1
Skewness0.9893713375
Sum420263
Variance1.210100643
MonotocityNot monotonic
2020-11-30T23:55:35.490680image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35983131.2%
 
42883015.0%
 
22708714.1%
 
5109725.7%
 
180194.2%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
180194.2%
 
22708714.1%
 
35983131.2%
 
42883015.0%
 
5109725.7%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5109725.7%
 
42883015.0%
 
35983131.2%
 
22708714.1%
 
180194.2%
 

KBA05_GBZ
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.630402736
Minimum0
Maximum5
Zeros2
Zeros (%)< 0.1%
Memory size1.5 MiB
2020-11-30T23:55:35.576640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.168496161
Coefficient of variation (CV)0.3218640592
Kurtosis-0.3469478714
Mean3.630402736
Median Absolute Deviation (MAD)1
Skewness-0.6267723131
Sum492544
Variance1.365383279
MonotocityNot monotonic
2020-11-30T23:55:35.656084image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
44301822.4%
 
53662919.1%
 
33471418.1%
 
2118766.2%
 
194334.9%
 
02< 0.1%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
02< 0.1%
 
194334.9%
 
2118766.2%
 
33471418.1%
 
44301822.4%
 
53662919.1%
 
ValueCountFrequency (%) 
53662919.1%
 
44301822.4%
 
33471418.1%
 
2118766.2%
 
194334.9%
 
02< 0.1%
 

KBA05_HERST1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.791873047
Minimum0
Maximum9
Zeros5354
Zeros (%)2.8%
Memory size1.5 MiB
2020-11-30T23:55:35.735456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.382876588
Coefficient of variation (CV)0.4953221602
Kurtosis1.626104281
Mean2.791873047
Median Absolute Deviation (MAD)1
Skewness0.5606794931
Sum378779
Variance1.912347659
MonotocityNot monotonic
2020-11-30T23:55:35.816207image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
23894820.3%
 
33809119.9%
 
42159311.3%
 
1154818.1%
 
5152728.0%
 
053542.8%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
053542.8%
 
1154818.1%
 
23894820.3%
 
33809119.9%
 
42159311.3%
 
5152728.0%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5152728.0%
 
42159311.3%
 
33809119.9%
 
23894820.3%
 
1154818.1%
 
053542.8%
 

KBA05_HERST2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.186457043
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:35.899996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.081791869
Coefficient of variation (CV)0.3394967685
Kurtosis4.485782146
Mean3.186457043
Median Absolute Deviation (MAD)1
Skewness0.9951617215
Sum432313
Variance1.170273649
MonotocityNot monotonic
2020-11-30T23:55:35.983938image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35797730.3%
 
43280917.1%
 
22624013.7%
 
5121396.3%
 
155742.9%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
155742.9%
 
22624013.7%
 
35797730.3%
 
43280917.1%
 
5121396.3%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5121396.3%
 
43280917.1%
 
35797730.3%
 
22624013.7%
 
155742.9%
 

KBA05_HERST3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.832507813
Minimum0
Maximum9
Zeros1918
Zeros (%)1.0%
Memory size1.5 MiB
2020-11-30T23:55:36.074419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.183915028
Coefficient of variation (CV)0.4179741439
Kurtosis3.972805518
Mean2.832507813
Median Absolute Deviation (MAD)1
Skewness0.8177614901
Sum384292
Variance1.401654794
MonotocityNot monotonic
2020-11-30T23:55:36.149184image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
35460628.5%
 
23303117.2%
 
42354912.3%
 
1140897.4%
 
575463.9%
 
019181.0%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
019181.0%
 
1140897.4%
 
23303117.2%
 
35460628.5%
 
42354912.3%
 
575463.9%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
575463.9%
 
42354912.3%
 
35460628.5%
 
23303117.2%
 
1140897.4%
 
019181.0%
 

KBA05_HERST4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.781775164
Minimum0
Maximum9
Zeros3323
Zeros (%)1.7%
Memory size1.5 MiB
2020-11-30T23:55:36.229276image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.251338051
Coefficient of variation (CV)0.4498343603
Kurtosis3.093951437
Mean2.781775164
Median Absolute Deviation (MAD)1
Skewness0.6926824009
Sum377409
Variance1.565846918
MonotocityNot monotonic
2020-11-30T23:55:36.304494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
34941425.8%
 
23423117.9%
 
42330312.2%
 
1158118.2%
 
586574.5%
 
033231.7%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
033231.7%
 
1158118.2%
 
23423117.9%
 
34941425.8%
 
42330312.2%
 
586574.5%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
586574.5%
 
42330312.2%
 
34941425.8%
 
23423117.9%
 
1158118.2%
 
033231.7%
 

KBA05_HERST5
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.637286986
Minimum0
Maximum9
Zeros6536
Zeros (%)3.4%
Memory size1.5 MiB
2020-11-30T23:55:36.384386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.281040486
Coefficient of variation (CV)0.4857417842
Kurtosis3.097299781
Mean2.637286986
Median Absolute Deviation (MAD)1
Skewness0.6075345583
Sum357806
Variance1.641064727
MonotocityNot monotonic
2020-11-30T23:55:36.458074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
34706024.6%
 
23612818.9%
 
42270211.8%
 
1166008.7%
 
065363.4%
 
557133.0%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
065363.4%
 
1166008.7%
 
23612818.9%
 
34706024.6%
 
42270211.8%
 
557133.0%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
557133.0%
 
42270211.8%
 
34706024.6%
 
23612818.9%
 
1166008.7%
 
065363.4%
 

KBA05_HERSTTEMP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean2.635900512
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:36.534947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.345302872
Coefficient of variation (CV)0.5103769531
Kurtosis2.926074855
Mean2.635900512
Median Absolute Deviation (MAD)1
Skewness1.10300346
Sum373573
Variance1.809839817
MonotocityNot monotonic
2020-11-30T23:55:36.618981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
23956520.6%
 
33691619.3%
 
13137516.4%
 
42218911.6%
 
5103895.4%
 
912910.7%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
13137516.4%
 
23956520.6%
 
33691619.3%
 
42218911.6%
 
5103895.4%
 
912910.7%
 
ValueCountFrequency (%) 
912910.7%
 
5103895.4%
 
42218911.6%
 
33691619.3%
 
23956520.6%
 
13137516.4%
 

KBA05_KRSAQUOT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.432882245
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:36.709451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.146147698
Coefficient of variation (CV)0.3338732924
Kurtosis2.703972222
Mean3.432882245
Median Absolute Deviation (MAD)1
Skewness0.5289774311
Sum465746
Variance1.313654545
MonotocityNot monotonic
2020-11-30T23:55:36.798312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35178427.0%
 
43755119.6%
 
52250511.7%
 
2163698.5%
 
165303.4%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
165303.4%
 
2163698.5%
 
35178427.0%
 
43755119.6%
 
52250511.7%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
52250511.7%
 
43755119.6%
 
35178427.0%
 
2163698.5%
 
165303.4%
 

KBA05_KRSHERST1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.153568901
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:36.884125image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.102287526
Coefficient of variation (CV)0.3495365284
Kurtosis4.176923227
Mean3.153568901
Median Absolute Deviation (MAD)1
Skewness0.8807288914
Sum427851
Variance1.215037789
MonotocityNot monotonic
2020-11-30T23:55:36.965275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35416228.3%
 
43564318.6%
 
22697414.1%
 
5106225.5%
 
173383.8%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
173383.8%
 
22697414.1%
 
35416228.3%
 
43564318.6%
 
5106225.5%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5106225.5%
 
43564318.6%
 
35416228.3%
 
22697414.1%
 
173383.8%
 

KBA05_KRSHERST2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.131596792
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:37.051681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.128022417
Coefficient of variation (CV)0.3602067863
Kurtosis3.820571144
Mean3.131596792
Median Absolute Deviation (MAD)1
Skewness0.839196906
Sum424870
Variance1.272434572
MonotocityNot monotonic
2020-11-30T23:55:37.130777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35624929.3%
 
43187316.6%
 
22564913.4%
 
5119926.3%
 
189764.7%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
189764.7%
 
22564913.4%
 
35624929.3%
 
43187316.6%
 
5119926.3%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5119926.3%
 
43187316.6%
 
35624929.3%
 
22564913.4%
 
189764.7%
 

KBA05_KRSHERST3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.94104163
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:37.217709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.164364988
Coefficient of variation (CV)0.3959022465
Kurtosis3.768932513
Mean2.94104163
Median Absolute Deviation (MAD)1
Skewness0.9626158155
Sum399017
Variance1.355745826
MonotocityNot monotonic
2020-11-30T23:55:37.297078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35470528.5%
 
23262917.0%
 
42381012.4%
 
1129926.8%
 
5106035.5%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1129926.8%
 
23262917.0%
 
35470528.5%
 
42381012.4%
 
5106035.5%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5106035.5%
 
42381012.4%
 
35470528.5%
 
23262917.0%
 
1129926.8%
 

KBA05_KRSKLEIN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Memory size1.5 MiB
2
85741 
1
26881 
3
22117 
9
 
933
ValueCountFrequency (%) 
28574144.7%
 
12688114.0%
 
32211711.5%
 
99330.5%
 
(Missing)5598029.2%
 
2020-11-30T23:55:37.397196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
28574114.9%
 
a559809.7%
 
1268814.7%
 
3221173.8%
 
99330.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27134447.2%
 
Lowercase Letter16794029.2%
 
Other Punctuation13567223.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
013567250.0%
 
28574131.6%
 
1268819.9%
 
3221178.2%
 
99330.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.135672100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common40701670.8%
 
Latin16794029.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
.13567233.3%
 
013567233.3%
 
28574121.1%
 
1268816.6%
 
3221175.4%
 
99330.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
28574114.9%
 
a559809.7%
 
1268814.7%
 
3221173.8%
 
99330.2%
 

KBA05_KRSOBER
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Memory size1.5 MiB
2
85619 
3
28364 
1
20756 
9
 
933
ValueCountFrequency (%) 
28561944.7%
 
32836414.8%
 
12075610.8%
 
99330.5%
 
(Missing)5598029.2%
 
2020-11-30T23:55:37.493274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
28561914.9%
 
a559809.7%
 
3283644.9%
 
1207563.6%
 
99330.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27134447.2%
 
Lowercase Letter16794029.2%
 
Other Punctuation13567223.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
013567250.0%
 
28561931.6%
 
32836410.5%
 
1207567.6%
 
99330.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.135672100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common40701670.8%
 
Latin16794029.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
.13567233.3%
 
013567233.3%
 
28561921.0%
 
3283647.0%
 
1207565.1%
 
99330.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
28561914.9%
 
a559809.7%
 
3283644.9%
 
1207563.6%
 
99330.2%
 

KBA05_KRSVAN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Memory size1.5 MiB
2
89816 
3
23317 
1
21606 
9
 
933
ValueCountFrequency (%) 
28981646.9%
 
32331712.2%
 
12160611.3%
 
99330.5%
 
(Missing)5598029.2%
 
2020-11-30T23:55:37.589638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
28981615.6%
 
a559809.7%
 
3233174.1%
 
1216063.8%
 
99330.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27134447.2%
 
Lowercase Letter16794029.2%
 
Other Punctuation13567223.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
013567250.0%
 
28981633.1%
 
3233178.6%
 
1216068.0%
 
99330.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.135672100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common40701670.8%
 
Latin16794029.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
.13567233.3%
 
013567233.3%
 
28981622.1%
 
3233175.7%
 
1216065.3%
 
99330.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
28981615.6%
 
a559809.7%
 
3233174.1%
 
1216063.8%
 
99330.2%
 

KBA05_KRSZUL
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Memory size1.5 MiB
2
75450 
3
32866 
1
26423 
9
 
933
ValueCountFrequency (%) 
27545039.4%
 
33286617.1%
 
12642313.8%
 
99330.5%
 
(Missing)5598029.2%
 
2020-11-30T23:55:39.251678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
27545013.1%
 
a559809.7%
 
3328665.7%
 
1264234.6%
 
99330.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27134447.2%
 
Lowercase Letter16794029.2%
 
Other Punctuation13567223.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
013567250.0%
 
27545027.8%
 
33286612.1%
 
1264239.7%
 
99330.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.135672100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common40701670.8%
 
Latin16794029.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
.13567233.3%
 
013567233.3%
 
27545018.5%
 
3328668.1%
 
1264236.5%
 
99330.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
27545013.1%
 
a559809.7%
 
3328665.7%
 
1264234.6%
 
99330.2%
 

KBA05_KW1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.764638245
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:39.340709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.145709034
Coefficient of variation (CV)0.4144155339
Kurtosis4.646652796
Mean2.764638245
Median Absolute Deviation (MAD)1
Skewness1.076300717
Sum375084
Variance1.312649191
MonotocityNot monotonic
2020-11-30T23:55:39.420981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35251227.4%
 
23626218.9%
 
42270211.8%
 
1176249.2%
 
556392.9%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1176249.2%
 
23626218.9%
 
35251227.4%
 
42270211.8%
 
556392.9%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
556392.9%
 
42270211.8%
 
35251227.4%
 
23626218.9%
 
1176249.2%
 

KBA05_KW2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.117489239
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:39.507570image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.084034674
Coefficient of variation (CV)0.3477268375
Kurtosis4.769373248
Mean3.117489239
Median Absolute Deviation (MAD)1
Skewness1.021033737
Sum422956
Variance1.175131174
MonotocityNot monotonic
2020-11-30T23:55:39.587871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
36073231.7%
 
42972215.5%
 
22638213.8%
 
5107025.6%
 
172013.8%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
172013.8%
 
22638213.8%
 
36073231.7%
 
42972215.5%
 
5107025.6%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5107025.6%
 
42972215.5%
 
36073231.7%
 
22638213.8%
 
172013.8%
 

KBA05_KW3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.820692553
Minimum0
Maximum9
Zeros20709
Zeros (%)10.8%
Memory size1.5 MiB
2020-11-30T23:55:39.677623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.373208414
Coefficient of variation (CV)0.7542231182
Kurtosis3.530311822
Mean1.820692553
Median Absolute Deviation (MAD)1
Skewness1.155774056
Sum247017
Variance1.885701349
MonotocityNot monotonic
2020-11-30T23:55:39.752462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
14342122.7%
 
23374917.6%
 
02070910.8%
 
31973910.3%
 
4171218.9%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
02070910.8%
 
14342122.7%
 
23374917.6%
 
31973910.3%
 
4171218.9%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
4171218.9%
 
31973910.3%
 
23374917.6%
 
14342122.7%
 
02070910.8%
 

KBA05_MAXAH
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.801086444
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:39.830604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q35
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.269736377
Coefficient of variation (CV)0.3340456462
Kurtosis0.4178195758
Mean3.801086444
Median Absolute Deviation (MAD)1
Skewness0.07048457009
Sum515701
Variance1.612230468
MonotocityNot monotonic
2020-11-30T23:55:39.909384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
55439428.4%
 
33370217.6%
 
22217611.6%
 
42180311.4%
 
126641.4%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
126641.4%
 
22217611.6%
 
33370217.6%
 
42180311.4%
 
55439428.4%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
55439428.4%
 
42180311.4%
 
33370217.6%
 
22217611.6%
 
126641.4%
 

KBA05_MAXBJ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.600669261
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:39.997774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.305333067
Coefficient of variation (CV)0.5019219808
Kurtosis2.012251827
Mean2.600669261
Median Absolute Deviation (MAD)1
Skewness0.6930555085
Sum352838
Variance1.703894415
MonotocityNot monotonic
2020-11-30T23:55:40.078561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
44335322.6%
 
13636719.0%
 
23039515.9%
 
32462412.8%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
13636719.0%
 
23039515.9%
 
32462412.8%
 
44335322.6%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
44335322.6%
 
32462412.8%
 
23039515.9%
 
13636719.0%
 

KBA05_MAXHERST
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.538998467
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:40.166707image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.175723947
Coefficient of variation (CV)0.4630660325
Kurtosis4.991627253
Mean2.538998467
Median Absolute Deviation (MAD)1
Skewness1.473583122
Sum344471
Variance1.382326799
MonotocityNot monotonic
2020-11-30T23:55:40.251164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
25763130.1%
 
33342017.4%
 
12033910.6%
 
4165328.6%
 
568173.6%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
12033910.6%
 
25763130.1%
 
33342017.4%
 
4165328.6%
 
568173.6%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
568173.6%
 
4165328.6%
 
33342017.4%
 
25763130.1%
 
12033910.6%
 

KBA05_MAXSEG
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.278495194
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:40.341199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.112225928
Coefficient of variation (CV)0.4881405633
Kurtosis7.362424319
Mean2.278495194
Median Absolute Deviation (MAD)1
Skewness1.654927924
Sum309128
Variance1.237046514
MonotocityNot monotonic
2020-11-30T23:55:40.417321image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
25249927.4%
 
13389317.7%
 
33154816.5%
 
4167998.8%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
13389317.7%
 
25249927.4%
 
33154816.5%
 
4167998.8%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
4167998.8%
 
33154816.5%
 
25249927.4%
 
13389317.7%
 

KBA05_MAXVORB
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Memory size1.5 MiB
2
65054 
1
45305 
3
24380 
9
 
933
ValueCountFrequency (%) 
26505433.9%
 
14530523.6%
 
32438012.7%
 
99330.5%
 
(Missing)5598029.2%
 
2020-11-30T23:55:40.514883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
26505411.3%
 
a559809.7%
 
1453057.9%
 
3243804.2%
 
99330.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27134447.2%
 
Lowercase Letter16794029.2%
 
Other Punctuation13567223.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
013567250.0%
 
26505424.0%
 
14530516.7%
 
3243809.0%
 
99330.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.135672100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common40701670.8%
 
Latin16794029.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
.13567233.3%
 
013567233.3%
 
26505416.0%
 
14530511.1%
 
3243806.0%
 
99330.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.13567223.6%
 
013567223.6%
 
n11196019.5%
 
26505411.3%
 
a559809.7%
 
1453057.9%
 
3243804.2%
 
99330.2%
 

KBA05_MOD1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.681245946
Minimum0
Maximum9
Zeros32586
Zeros (%)17.0%
Memory size1.5 MiB
2020-11-30T23:55:40.599413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.387115574
Coefficient of variation (CV)0.8250521448
Kurtosis3.671424746
Mean1.681245946
Median Absolute Deviation (MAD)1
Skewness1.103421243
Sum228098
Variance1.924089615
MonotocityNot monotonic
2020-11-30T23:55:40.673951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
23878320.2%
 
03258617.0%
 
12988715.6%
 
32168411.3%
 
4117996.2%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
03258617.0%
 
12988715.6%
 
23878320.2%
 
32168411.3%
 
4117996.2%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
4117996.2%
 
32168411.3%
 
23878320.2%
 
12988715.6%
 
03258617.0%
 

KBA05_MOD2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.044172711
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:40.753029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.078154428
Coefficient of variation (CV)0.3541699276
Kurtosis5.167665521
Mean3.044172711
Median Absolute Deviation (MAD)1
Skewness1.050445188
Sum413009
Variance1.162416972
MonotocityNot monotonic
2020-11-30T23:55:40.832914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35963131.1%
 
42994015.6%
 
22874315.0%
 
184134.4%
 
580124.2%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
184134.4%
 
22874315.0%
 
35963131.1%
 
42994015.6%
 
580124.2%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
580124.2%
 
42994015.6%
 
35963131.1%
 
22874315.0%
 
184134.4%
 

KBA05_MOD3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.076766024
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:40.920519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.117152643
Coefficient of variation (CV)0.363093142
Kurtosis4.12444309
Mean3.076766024
Median Absolute Deviation (MAD)1
Skewness0.9233859669
Sum417431
Variance1.248030027
MonotocityNot monotonic
2020-11-30T23:55:41.002799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35305527.7%
 
43288017.2%
 
23052115.9%
 
597565.1%
 
185274.4%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
185274.4%
 
23052115.9%
 
35305527.7%
 
43288017.2%
 
597565.1%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
597565.1%
 
43288017.2%
 
35305527.7%
 
23052115.9%
 
185274.4%
 

KBA05_MOD4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.759272363
Minimum0
Maximum9
Zeros5107
Zeros (%)2.7%
Memory size1.5 MiB
2020-11-30T23:55:41.091244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.360023721
Coefficient of variation (CV)0.4928921623
Kurtosis1.861920435
Mean2.759272363
Median Absolute Deviation (MAD)1
Skewness0.5176912715
Sum374356
Variance1.849664522
MonotocityNot monotonic
2020-11-30T23:55:41.163639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
34341422.7%
 
23121416.3%
 
42399112.5%
 
11943510.1%
 
5115786.0%
 
051072.7%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
051072.7%
 
11943510.1%
 
23121416.3%
 
34341422.7%
 
42399112.5%
 
5115786.0%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5115786.0%
 
42399112.5%
 
34341422.7%
 
23121416.3%
 
11943510.1%
 
051072.7%
 

KBA05_MOD8
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.446024235
Minimum0
Maximum9
Zeros26798
Zeros (%)14.0%
Memory size1.5 MiB
2020-11-30T23:55:41.242821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.133160562
Coefficient of variation (CV)0.7836387072
Kurtosis11.58649262
Mean1.446024235
Median Absolute Deviation (MAD)1
Skewness1.976300412
Sum196185
Variance1.284052859
MonotocityNot monotonic
2020-11-30T23:55:41.318493image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
14551523.7%
 
24500523.5%
 
02679814.0%
 
3174219.1%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
02679814.0%
 
14551523.7%
 
24500523.5%
 
3174219.1%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
3174219.1%
 
24500523.5%
 
14551523.7%
 
02679814.0%
 

KBA05_MODTEMP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean2.912831187
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:41.395170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.24516257
Coefficient of variation (CV)0.4274750199
Kurtosis-0.8770609878
Mean2.912831187
Median Absolute Deviation (MAD)1
Skewness-0.1790883695
Sum412821
Variance1.550429825
MonotocityNot monotonic
2020-11-30T23:55:41.475281image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34564923.8%
 
43932220.5%
 
12914915.2%
 
2164518.6%
 
5103895.4%
 
67650.4%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
12914915.2%
 
2164518.6%
 
34564923.8%
 
43932220.5%
 
5103895.4%
 
67650.4%
 
ValueCountFrequency (%) 
67650.4%
 
5103895.4%
 
43932220.5%
 
34564923.8%
 
2164518.6%
 
12914915.2%
 

KBA05_MOTOR
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.814353735
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:41.552573image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.045461907
Coefficient of variation (CV)0.3714749478
Kurtosis6.838946521
Mean2.814353735
Median Absolute Deviation (MAD)1
Skewness1.085054329
Sum381829
Variance1.092990599
MonotocityNot monotonic
2020-11-30T23:55:41.629983image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35835730.4%
 
23208716.7%
 
42996415.6%
 
1143317.5%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1143317.5%
 
23208716.7%
 
35835730.4%
 
42996415.6%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
42996415.6%
 
35835730.4%
 
23208716.7%
 
1143317.5%
 

KBA05_MOTRAD
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.247280205
Minimum0
Maximum9
Zeros26539
Zeros (%)13.8%
Memory size1.5 MiB
2020-11-30T23:55:41.715155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.098360746
Coefficient of variation (CV)0.8806046483
Kurtosis14.26590566
Mean1.247280205
Median Absolute Deviation (MAD)0
Skewness2.563152731
Sum169221
Variance1.206396329
MonotocityNot monotonic
2020-11-30T23:55:41.786571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
17329938.2%
 
02653913.8%
 
3181159.5%
 
2168428.8%
 
98770.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
02653913.8%
 
17329938.2%
 
2168428.8%
 
3181159.5%
 
98770.5%
 
ValueCountFrequency (%) 
98770.5%
 
3181159.5%
 
2168428.8%
 
17329938.2%
 
02653913.8%
 

KBA05_SEG1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.158470429
Minimum0
Maximum9
Zeros36867
Zeros (%)19.2%
Memory size1.5 MiB
2020-11-30T23:55:41.864850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.087014368
Coefficient of variation (CV)0.9383186153
Kurtosis16.5594327
Mean1.158470429
Median Absolute Deviation (MAD)1
Skewness2.660928562
Sum157172
Variance1.181600237
MonotocityNot monotonic
2020-11-30T23:55:41.938837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
15508628.7%
 
03686719.2%
 
23466918.1%
 
381174.2%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
03686719.2%
 
15508628.7%
 
23466918.1%
 
381174.2%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
381174.2%
 
23466918.1%
 
15508628.7%
 
03686719.2%
 

KBA05_SEG10
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.162701221
Minimum0
Maximum9
Zeros9635
Zeros (%)5.0%
Memory size1.5 MiB
2020-11-30T23:55:42.021554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.193768704
Coefficient of variation (CV)0.551980409
Kurtosis5.95690075
Mean2.162701221
Median Absolute Deviation (MAD)1
Skewness1.14716283
Sum293418
Variance1.425083719
MonotocityNot monotonic
2020-11-30T23:55:42.094033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
25341327.9%
 
33275917.1%
 
12527013.2%
 
4136627.1%
 
096355.0%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
096355.0%
 
12527013.2%
 
25341327.9%
 
33275917.1%
 
4136627.1%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
4136627.1%
 
33275917.1%
 
25341327.9%
 
12527013.2%
 
096355.0%
 

KBA05_SEG2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.921184917
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:42.170884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.090809521
Coefficient of variation (CV)0.3734133759
Kurtosis5.347360956
Mean2.921184917
Median Absolute Deviation (MAD)1
Skewness1.076245236
Sum396323
Variance1.189865412
MonotocityNot monotonic
2020-11-30T23:55:42.252694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35898630.8%
 
23154016.5%
 
42656913.9%
 
1116526.1%
 
559923.1%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1116526.1%
 
23154016.5%
 
35898630.8%
 
42656913.9%
 
559923.1%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
559923.1%
 
42656913.9%
 
35898630.8%
 
23154016.5%
 
1116526.1%
 

KBA05_SEG3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.890264756
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:42.340050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.092004989
Coefficient of variation (CV)0.377821785
Kurtosis5.38632872
Mean2.890264756
Median Absolute Deviation (MAD)1
Skewness1.196567801
Sum392128
Variance1.192474897
MonotocityNot monotonic
2020-11-30T23:55:42.419868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35435528.4%
 
23834620.0%
 
42555613.3%
 
1101655.3%
 
563173.3%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1101655.3%
 
23834620.0%
 
35435528.4%
 
42555613.3%
 
563173.3%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
563173.3%
 
42555613.3%
 
35435528.4%
 
23834620.0%
 
1101655.3%
 

KBA05_SEG4
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.049848163
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:42.505075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.068621911
Coefficient of variation (CV)0.3503852828
Kurtosis5.439691246
Mean3.049848163
Median Absolute Deviation (MAD)1
Skewness1.123933236
Sum413779
Variance1.141952789
MonotocityNot monotonic
2020-11-30T23:55:42.585697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
36348133.1%
 
22773814.5%
 
42671313.9%
 
589514.7%
 
178564.1%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
178564.1%
 
22773814.5%
 
36348133.1%
 
42671313.9%
 
589514.7%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
589514.7%
 
42671313.9%
 
36348133.1%
 
22773814.5%
 
178564.1%
 

KBA05_SEG5
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.784229613
Minimum0
Maximum9
Zeros18467
Zeros (%)9.6%
Memory size1.5 MiB
2020-11-30T23:55:42.674822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.29501673
Coefficient of variation (CV)0.7258128221
Kurtosis5.052159987
Mean1.784229613
Median Absolute Deviation (MAD)1
Skewness1.340142636
Sum242070
Variance1.677068332
MonotocityNot monotonic
2020-11-30T23:55:42.749199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
14443023.2%
 
23841920.0%
 
32128711.1%
 
0184679.6%
 
4121366.3%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
0184679.6%
 
14443023.2%
 
23841920.0%
 
32128711.1%
 
4121366.3%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
4121366.3%
 
32128711.1%
 
23841920.0%
 
14443023.2%
 
0184679.6%
 

KBA05_SEG6
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Memory size1.5 MiB
0
111010 
1
23729 
9
 
933
ValueCountFrequency (%) 
011101057.9%
 
12372912.4%
 
99330.5%
 
(Missing)5598029.2%
 
2020-11-30T23:55:42.842924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
024668242.9%
 
.13567223.6%
 
n11196019.5%
 
a559809.7%
 
1237294.1%
 
99330.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27134447.2%
 
Lowercase Letter16794029.2%
 
Other Punctuation13567223.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
024668290.9%
 
1237298.7%
 
99330.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.135672100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common40701670.8%
 
Latin16794029.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
024668260.6%
 
.13567233.3%
 
1237295.8%
 
99330.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n11196066.7%
 
a5598033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
024668242.9%
 
.13567223.6%
 
n11196019.5%
 
a559809.7%
 
1237294.1%
 
99330.2%
 

KBA05_SEG7
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.001776343
Minimum0
Maximum9
Zeros53730
Zeros (%)28.0%
Memory size1.5 MiB
2020-11-30T23:55:42.928822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.142617306
Coefficient of variation (CV)1.140591225
Kurtosis14.46354036
Mean1.001776343
Median Absolute Deviation (MAD)1
Skewness2.574614929
Sum135913
Variance1.305574308
MonotocityNot monotonic
2020-11-30T23:55:43.002860image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
05373028.0%
 
14309222.5%
 
22932715.3%
 
385904.5%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
05373028.0%
 
14309222.5%
 
22932715.3%
 
385904.5%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
385904.5%
 
22932715.3%
 
14309222.5%
 
05373028.0%
 

KBA05_SEG8
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.000169527
Minimum0
Maximum9
Zeros54785
Zeros (%)28.6%
Memory size1.5 MiB
2020-11-30T23:55:43.081072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.154433461
Coefficient of variation (CV)1.154237787
Kurtosis13.83319917
Mean1.000169527
Median Absolute Deviation (MAD)1
Skewness2.525128375
Sum135695
Variance1.332716617
MonotocityNot monotonic
2020-11-30T23:55:43.153681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
05478528.6%
 
14209522.0%
 
22837414.8%
 
394854.9%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
05478528.6%
 
14209522.0%
 
22837414.8%
 
394854.9%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
394854.9%
 
22837414.8%
 
14209522.0%
 
05478528.6%
 

KBA05_SEG9
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean1.237049649
Minimum0
Maximum9
Zeros34324
Zeros (%)17.9%
Memory size1.5 MiB
2020-11-30T23:55:43.232744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.106325155
Coefficient of variation (CV)0.8943255885
Kurtosis14.62241571
Mean1.237049649
Median Absolute Deviation (MAD)1
Skewness2.418843164
Sum167833
Variance1.22395535
MonotocityNot monotonic
2020-11-30T23:55:43.304369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
15170527.0%
 
23839920.0%
 
03432417.9%
 
3103115.4%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
03432417.9%
 
15170527.0%
 
23839920.0%
 
3103115.4%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
3103115.4%
 
23839920.0%
 
15170527.0%
 
03432417.9%
 

KBA05_VORB0
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.305074002
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:43.378531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.15624528
Coefficient of variation (CV)0.3498394528
Kurtosis2.801743753
Mean3.305074002
Median Absolute Deviation (MAD)1
Skewness0.5879478751
Sum448406
Variance1.336903148
MonotocityNot monotonic
2020-11-30T23:55:43.456475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34685524.4%
 
44044321.1%
 
22326312.1%
 
5167428.7%
 
174363.9%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
174363.9%
 
22326312.1%
 
34685524.4%
 
44044321.1%
 
5167428.7%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5167428.7%
 
44044321.1%
 
34685524.4%
 
22326312.1%
 
174363.9%
 

KBA05_VORB1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.025930185
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:43.540275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.101034329
Coefficient of variation (CV)0.3638664019
Kurtosis4.755839511
Mean3.025930185
Median Absolute Deviation (MAD)1
Skewness1.023447839
Sum410534
Variance1.212276593
MonotocityNot monotonic
2020-11-30T23:55:43.620639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
36028531.5%
 
22862714.9%
 
42698714.1%
 
195305.0%
 
593104.9%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
195305.0%
 
22862714.9%
 
36028531.5%
 
42698714.1%
 
593104.9%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
593104.9%
 
42698714.1%
 
36028531.5%
 
22862714.9%
 
195305.0%
 

KBA05_VORB2
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.306968276
Minimum0
Maximum9
Zeros11641
Zeros (%)6.1%
Memory size1.5 MiB
2020-11-30T23:55:43.710172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.345094423
Coefficient of variation (CV)0.5830571824
Kurtosis2.980059335
Mean2.306968276
Median Absolute Deviation (MAD)1
Skewness0.7745051864
Sum312991
Variance1.809279007
MonotocityNot monotonic
2020-11-30T23:55:43.788699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
34112321.5%
 
23790319.8%
 
12524213.2%
 
4139737.3%
 
0116416.1%
 
548572.5%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
0116416.1%
 
12524213.2%
 
23790319.8%
 
34112321.5%
 
4139737.3%
 
548572.5%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
548572.5%
 
4139737.3%
 
34112321.5%
 
23790319.8%
 
12524213.2%
 
0116416.1%
 

KBA05_ZUL1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.785217289
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:43.869884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.076782703
Coefficient of variation (CV)0.3866063545
Kurtosis6.259647492
Mean2.785217289
Median Absolute Deviation (MAD)1
Skewness1.216591826
Sum377876
Variance1.159460989
MonotocityNot monotonic
2020-11-30T23:55:43.954827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35887430.7%
 
23571218.6%
 
42211611.5%
 
1143047.5%
 
537331.9%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1143047.5%
 
23571218.6%
 
35887430.7%
 
42211611.5%
 
537331.9%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
537331.9%
 
42211611.5%
 
35887430.7%
 
23571218.6%
 
1143047.5%
 

KBA05_ZUL2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.088161153
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:44.042165image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.086680768
Coefficient of variation (CV)0.3518860298
Kurtosis4.76578942
Mean3.088161153
Median Absolute Deviation (MAD)1
Skewness1.030775698
Sum418977
Variance1.180875091
MonotocityNot monotonic
2020-11-30T23:55:44.122586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35782830.2%
 
43083816.1%
 
22915115.2%
 
596305.0%
 
172923.8%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
172923.8%
 
22915115.2%
 
35782830.2%
 
43083816.1%
 
596305.0%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
596305.0%
 
43083816.1%
 
35782830.2%
 
22915115.2%
 
172923.8%
 

KBA05_ZUL3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.969124064
Minimum0
Maximum9
Zeros5137
Zeros (%)2.7%
Memory size1.5 MiB
2020-11-30T23:55:44.212375image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.306666695
Coefficient of variation (CV)0.4400849097
Kurtosis2.204287452
Mean2.969124064
Median Absolute Deviation (MAD)1
Skewness0.2948038427
Sum402827
Variance1.707377853
MonotocityNot monotonic
2020-11-30T23:55:44.287301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
34548223.7%
 
43368117.6%
 
22782914.5%
 
1113625.9%
 
5112485.9%
 
051372.7%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
051372.7%
 
1113625.9%
 
22782914.5%
 
34548223.7%
 
43368117.6%
 
5112485.9%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5112485.9%
 
43368117.6%
 
34548223.7%
 
22782914.5%
 
1113625.9%
 
051372.7%
 

KBA05_ZUL4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean2.45306327
Minimum0
Maximum9
Zeros8776
Zeros (%)4.6%
Memory size1.5 MiB
2020-11-30T23:55:44.365700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.470194643
Coefficient of variation (CV)0.5993300952
Kurtosis1.32264108
Mean2.45306327
Median Absolute Deviation (MAD)1
Skewness0.6872581693
Sum332812
Variance2.161472289
MonotocityNot monotonic
2020-11-30T23:55:44.444794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
23620718.9%
 
13021415.8%
 
32690014.0%
 
42212311.5%
 
5105195.5%
 
087764.6%
 
99330.5%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
087764.6%
 
13021415.8%
 
23620718.9%
 
32690014.0%
 
42212311.5%
 
5105195.5%
 
99330.5%
 
ValueCountFrequency (%) 
99330.5%
 
5105195.5%
 
42212311.5%
 
32690014.0%
 
23620718.9%
 
13021415.8%
 
087764.6%
 

KBA13_ALTERHALTER_30
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.625620677
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:44.532468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9672547771
Coefficient of variation (CV)0.3683909049
Kurtosis-0.1729162769
Mean2.625620677
Median Absolute Deviation (MAD)1
Skewness0.08545307631
Sum368561
Variance0.9355818038
MonotocityNot monotonic
2020-11-30T23:55:44.614889image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36269232.7%
 
23765219.6%
 
11984210.4%
 
4155868.1%
 
545992.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
11984210.4%
 
23765219.6%
 
36269232.7%
 
4155868.1%
 
545992.4%
 
ValueCountFrequency (%) 
545992.4%
 
4155868.1%
 
36269232.7%
 
23765219.6%
 
11984210.4%
 

KBA13_ALTERHALTER_45
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.004203147
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:44.704802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.048776652
Coefficient of variation (CV)0.3491031066
Kurtosis-0.3977563254
Mean3.004203147
Median Absolute Deviation (MAD)1
Skewness-0.0246833239
Sum421703
Variance1.099932465
MonotocityNot monotonic
2020-11-30T23:55:44.786955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35783930.2%
 
43002315.7%
 
22855314.9%
 
1121986.4%
 
5117586.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1121986.4%
 
22855314.9%
 
35783930.2%
 
43002315.7%
 
5117586.1%
 
ValueCountFrequency (%) 
5117586.1%
 
43002315.7%
 
35783930.2%
 
22855314.9%
 
1121986.4%
 

KBA13_ALTERHALTER_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.926081598
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:44.876637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.02150079
Coefficient of variation (CV)0.3491019495
Kurtosis-0.3134614298
Mean2.926081598
Median Absolute Deviation (MAD)1
Skewness0.0748532631
Sum410737
Variance1.043463865
MonotocityNot monotonic
2020-11-30T23:55:44.962588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35934631.0%
 
23283817.1%
 
42611613.6%
 
1119496.2%
 
5101225.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1119496.2%
 
23283817.1%
 
35934631.0%
 
42611613.6%
 
5101225.3%
 
ValueCountFrequency (%) 
5101225.3%
 
42611613.6%
 
35934631.0%
 
23283817.1%
 
1119496.2%
 

KBA13_ALTERHALTER_61
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.271623056
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:45.053177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.029103999
Coefficient of variation (CV)0.3145545748
Kurtosis-0.4112272787
Mean3.271623056
Median Absolute Deviation (MAD)1
Skewness-0.05458832122
Sum459241
Variance1.059055041
MonotocityNot monotonic
2020-11-30T23:55:45.135925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35786730.2%
 
43465218.1%
 
22234811.7%
 
51920810.0%
 
162963.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
162963.3%
 
22234811.7%
 
35786730.2%
 
43465218.1%
 
51920810.0%
 
ValueCountFrequency (%) 
51920810.0%
 
43465218.1%
 
35786730.2%
 
22234811.7%
 
162963.3%
 

KBA13_ANTG1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.405881557
Minimum0
Maximum4
Zeros532
Zeros (%)0.3%
Memory size1.5 MiB
2020-11-30T23:55:45.226481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.858057968
Coefficient of variation (CV)0.3566501292
Kurtosis-0.4939552431
Mean2.405881557
Median Absolute Deviation (MAD)1
Skewness0.02696690775
Sum337716
Variance0.7362634764
MonotocityNot monotonic
2020-11-30T23:55:45.308911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
25741230.0%
 
34927325.7%
 
11918110.0%
 
4139737.3%
 
05320.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
05320.3%
 
11918110.0%
 
25741230.0%
 
34927325.7%
 
4139737.3%
 
ValueCountFrequency (%) 
4139737.3%
 
34927325.7%
 
25741230.0%
 
11918110.0%
 
05320.3%
 

KBA13_ANTG2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.753075778
Minimum0
Maximum4
Zeros941
Zeros (%)0.5%
Memory size1.5 MiB
2020-11-30T23:55:45.398014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8520218026
Coefficient of variation (CV)0.3094799677
Kurtosis-0.08057928726
Mean2.753075778
Median Absolute Deviation (MAD)1
Skewness-0.3963905462
Sum386452
Variance0.7259411522
MonotocityNot monotonic
2020-11-30T23:55:45.480446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36482433.8%
 
23953020.6%
 
42594813.5%
 
191284.8%
 
09410.5%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
09410.5%
 
191284.8%
 
23953020.6%
 
36482433.8%
 
42594813.5%
 
ValueCountFrequency (%) 
42594813.5%
 
36482433.8%
 
23953020.6%
 
191284.8%
 
09410.5%
 

KBA13_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
1
49583 
2
47973 
0
25498 
3
17317 
ValueCountFrequency (%) 
14958325.9%
 
24797325.0%
 
02549813.3%
 
3173179.0%
 
(Missing)5128126.8%
 
2020-11-30T23:55:45.586979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
016586928.8%
 
.14037124.4%
 
n10256217.8%
 
a512818.9%
 
1495838.6%
 
2479738.3%
 
3173173.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
016586959.1%
 
14958317.7%
 
24797317.1%
 
3173176.2%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
016586939.4%
 
.14037133.3%
 
14958311.8%
 
24797311.4%
 
3173174.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
016586928.8%
 
.14037124.4%
 
n10256217.8%
 
a512818.9%
 
1495838.6%
 
2479738.3%
 
3173173.0%
 

KBA13_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
0
78976 
1
49804 
2
11591 
ValueCountFrequency (%) 
07897641.2%
 
14980426.0%
 
2115916.0%
 
(Missing)5128126.8%
 
2020-11-30T23:55:45.690235image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
021934738.2%
 
.14037124.4%
 
n10256217.8%
 
a512818.9%
 
1498048.7%
 
2115912.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
021934778.1%
 
14980417.7%
 
2115914.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
021934752.1%
 
.14037133.3%
 
14980411.8%
 
2115912.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
021934738.2%
 
.14037124.4%
 
n10256217.8%
 
a512818.9%
 
1498048.7%
 
2115912.0%
 

KBA13_ANZAHL_PKW
Real number (ℝ≥0)

MISSING

Distinct1250
Distinct (%)0.9%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean667.2312158
Minimum5
Maximum2300
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:45.796304image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile247
Q1430
median593
Q3828
95-th percentile1400
Maximum2300
Range2295
Interquartile range (IQR)398

Descriptive statistics

Standard deviation340.4817224
Coefficient of variation (CV)0.5102904575
Kurtosis1.749850177
Mean667.2312158
Median Absolute Deviation (MAD)189
Skewness1.204304691
Sum93659913
Variance115927.8033
MonotocityNot monotonic
2020-11-30T23:55:45.915251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
140024891.3%
 
150017180.9%
 
130014130.7%
 
160012640.7%
 
17007960.4%
 
18005990.3%
 
19003320.2%
 
5233020.2%
 
4642940.2%
 
5522830.1%
 
4912770.1%
 
5362760.1%
 
5842740.1%
 
5302710.1%
 
5342700.1%
 
5162700.1%
 
5102700.1%
 
4182690.1%
 
4702660.1%
 
4832650.1%
 
5192610.1%
 
6332610.1%
 
5432580.1%
 
5012580.1%
 
5622580.1%
 
Other values (1225)12687766.2%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
52< 0.1%
 
62< 0.1%
 
81< 0.1%
 
102< 0.1%
 
111< 0.1%
 
124< 0.1%
 
131< 0.1%
 
143< 0.1%
 
151< 0.1%
 
161< 0.1%
 
ValueCountFrequency (%) 
230083< 0.1%
 
220057< 0.1%
 
21001200.1%
 
20002540.1%
 
19003320.2%
 
18005990.3%
 
17007960.4%
 
160012640.7%
 
150017180.9%
 
140024891.3%
 

KBA13_AUDI
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.21893411
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:46.015546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9703509379
Coefficient of variation (CV)0.3014510098
Kurtosis-0.2117959836
Mean3.21893411
Median Absolute Deviation (MAD)1
Skewness-0.01706388144
Sum451845
Variance0.9415809427
MonotocityNot monotonic
2020-11-30T23:55:46.098489image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36259832.7%
 
43483818.2%
 
22256011.8%
 
5148017.7%
 
155742.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
155742.9%
 
22256011.8%
 
36259832.7%
 
43483818.2%
 
5148017.7%
 
ValueCountFrequency (%) 
5148017.7%
 
43483818.2%
 
36259832.7%
 
22256011.8%
 
155742.9%
 

KBA13_AUTOQUOTE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.990147538
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:46.189057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9611435495
Coefficient of variation (CV)0.3214368313
Kurtosis-0.07135772976
Mean2.990147538
Median Absolute Deviation (MAD)1
Skewness0.007477479812
Sum419730
Variance0.9237969227
MonotocityNot monotonic
2020-11-30T23:55:46.273908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36597734.4%
 
22842014.8%
 
42754314.4%
 
193424.9%
 
590894.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
193424.9%
 
22842014.8%
 
36597734.4%
 
42754314.4%
 
590894.7%
 
ValueCountFrequency (%) 
590894.7%
 
42754314.4%
 
36597734.4%
 
22842014.8%
 
193424.9%
 

KBA13_BAUMAX
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean1.630358122
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:46.364544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.249188358
Coefficient of variation (CV)0.766204885
Kurtosis2.119414622
Mean1.630358122
Median Absolute Deviation (MAD)0
Skewness1.890580313
Sum228855
Variance1.560471553
MonotocityNot monotonic
2020-11-30T23:55:46.445786image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
110396054.2%
 
2133287.0%
 
5121056.3%
 
361983.2%
 
447802.5%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
110396054.2%
 
2133287.0%
 
361983.2%
 
447802.5%
 
5121056.3%
 
ValueCountFrequency (%) 
5121056.3%
 
447802.5%
 
361983.2%
 
2133287.0%
 
110396054.2%
 

KBA13_BJ_1999
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.78960754
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:46.537546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9371101269
Coefficient of variation (CV)0.3359290199
Kurtosis-0.071183037
Mean2.78960754
Median Absolute Deviation (MAD)1
Skewness0.06150853483
Sum391580
Variance0.8781753899
MonotocityNot monotonic
2020-11-30T23:55:46.623799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36453733.7%
 
23666319.1%
 
42128811.1%
 
1124816.5%
 
554022.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1124816.5%
 
23666319.1%
 
36453733.7%
 
42128811.1%
 
554022.8%
 
ValueCountFrequency (%) 
554022.8%
 
42128811.1%
 
36453733.7%
 
23666319.1%
 
1124816.5%
 

KBA13_BJ_2000
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.715938477
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:46.714124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9507998262
Coefficient of variation (CV)0.3500815037
Kurtosis-0.164032874
Mean2.715938477
Median Absolute Deviation (MAD)1
Skewness0.04858109479
Sum381239
Variance0.9040203095
MonotocityNot monotonic
2020-11-30T23:55:46.797047image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36284632.8%
 
23764619.6%
 
41964610.3%
 
1155858.1%
 
546482.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1155858.1%
 
23764619.6%
 
36284632.8%
 
41964610.3%
 
546482.4%
 
ValueCountFrequency (%) 
546482.4%
 
41964610.3%
 
36284632.8%
 
23764619.6%
 
1155858.1%
 

KBA13_BJ_2004
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.024534982
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:46.887706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9194048485
Coefficient of variation (CV)0.3039822167
Kurtosis0.003106790911
Mean3.024534982
Median Absolute Deviation (MAD)1
Skewness0.0166127067
Sum424557
Variance0.8453052755
MonotocityNot monotonic
2020-11-30T23:55:46.972683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36739935.2%
 
42939615.3%
 
22832014.8%
 
582204.3%
 
170363.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
170363.7%
 
22832014.8%
 
36739935.2%
 
42939615.3%
 
582204.3%
 
ValueCountFrequency (%) 
582204.3%
 
42939615.3%
 
36739935.2%
 
22832014.8%
 
170363.7%
 

KBA13_BJ_2006
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.120259883
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:47.064263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9115819441
Coefficient of variation (CV)0.2921493652
Kurtosis-0.01423886238
Mean3.120259883
Median Absolute Deviation (MAD)1
Skewness0.002988399655
Sum437994
Variance0.8309816408
MonotocityNot monotonic
2020-11-30T23:55:47.148011image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36695434.9%
 
43331217.4%
 
22501913.1%
 
596905.1%
 
153962.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
153962.8%
 
22501913.1%
 
36695434.9%
 
43331217.4%
 
596905.1%
 
ValueCountFrequency (%) 
596905.1%
 
43331217.4%
 
36695434.9%
 
22501913.1%
 
153962.8%
 

KBA13_BJ_2008
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.698805309
Minimum0
Maximum5
Zeros19625
Zeros (%)10.2%
Memory size1.5 MiB
2020-11-30T23:55:47.236230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.474305083
Coefficient of variation (CV)0.5462806368
Kurtosis-0.5096319439
Mean2.698805309
Median Absolute Deviation (MAD)1
Skewness-0.3776022473
Sum378834
Variance2.173575477
MonotocityNot monotonic
2020-11-30T23:55:47.318950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35266327.5%
 
22420612.6%
 
01962510.2%
 
41950010.2%
 
5175149.1%
 
168633.6%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
01962510.2%
 
168633.6%
 
22420612.6%
 
35266327.5%
 
41950010.2%
 
5175149.1%
 
ValueCountFrequency (%) 
5175149.1%
 
41950010.2%
 
35266327.5%
 
22420612.6%
 
168633.6%
 
01962510.2%
 

KBA13_BJ_2009
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.694046491
Minimum0
Maximum5
Zeros16351
Zeros (%)8.5%
Memory size1.5 MiB
2020-11-30T23:55:47.396095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.469412712
Coefficient of variation (CV)0.5454296043
Kurtosis-0.6337266346
Mean2.694046491
Median Absolute Deviation (MAD)1
Skewness-0.3194372109
Sum378166
Variance2.159173717
MonotocityNot monotonic
2020-11-30T23:55:47.478080image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35509328.7%
 
4190109.9%
 
5175989.2%
 
2165388.6%
 
0163518.5%
 
1157818.2%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
0163518.5%
 
1157818.2%
 
2165388.6%
 
35509328.7%
 
4190109.9%
 
5175989.2%
 
ValueCountFrequency (%) 
5175989.2%
 
4190109.9%
 
35509328.7%
 
2165388.6%
 
1157818.2%
 
0163518.5%
 

KBA13_BMW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.465651737
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:47.559248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9486462755
Coefficient of variation (CV)0.2737281029
Kurtosis-0.3513243248
Mean3.465651737
Median Absolute Deviation (MAD)1
Skewness-0.0463869427
Sum486477
Variance0.899929756
MonotocityNot monotonic
2020-11-30T23:55:47.643227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35984431.2%
 
44028721.0%
 
52268211.8%
 
2148297.7%
 
127291.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
127291.4%
 
2148297.7%
 
35984431.2%
 
44028721.0%
 
52268211.8%
 
ValueCountFrequency (%) 
52268211.8%
 
44028721.0%
 
35984431.2%
 
2148297.7%
 
127291.4%
 

KBA13_CCM_0_1400
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.12568123
Minimum0
Maximum5
Zeros28511
Zeros (%)14.9%
Memory size1.5 MiB
2020-11-30T23:55:47.729592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.392846325
Coefficient of variation (CV)0.6552470358
Kurtosis-0.7052963514
Mean2.12568123
Median Absolute Deviation (MAD)1
Skewness-0.08564161896
Sum298384
Variance1.940020886
MonotocityNot monotonic
2020-11-30T23:55:47.809611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34496723.5%
 
23709019.4%
 
02851114.9%
 
1121556.3%
 
4110925.8%
 
565563.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02851114.9%
 
1121556.3%
 
23709019.4%
 
34496723.5%
 
4110925.8%
 
565563.4%
 
ValueCountFrequency (%) 
565563.4%
 
4110925.8%
 
34496723.5%
 
23709019.4%
 
1121556.3%
 
02851114.9%
 

KBA13_CCM_1000
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.248626853
Minimum0
Maximum5
Zeros19982
Zeros (%)10.4%
Memory size1.5 MiB
2020-11-30T23:55:47.885036image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.389220869
Coefficient of variation (CV)0.6178085379
Kurtosis-0.76400977
Mean2.248626853
Median Absolute Deviation (MAD)1
Skewness-0.05594406889
Sum315642
Variance1.929934622
MonotocityNot monotonic
2020-11-30T23:55:47.967048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35153426.9%
 
12576113.4%
 
22257811.8%
 
01998210.4%
 
4124576.5%
 
580594.2%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
01998210.4%
 
12576113.4%
 
22257811.8%
 
35153426.9%
 
4124576.5%
 
580594.2%
 
ValueCountFrequency (%) 
580594.2%
 
4124576.5%
 
35153426.9%
 
22257811.8%
 
12576113.4%
 
01998210.4%
 

KBA13_CCM_1200
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.147701448
Minimum0
Maximum5
Zeros29378
Zeros (%)15.3%
Memory size1.5 MiB
2020-11-30T23:55:48.043979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.429985286
Coefficient of variation (CV)0.6658212606
Kurtosis-0.8115685174
Mean2.147701448
Median Absolute Deviation (MAD)1
Skewness-0.09900420865
Sum301475
Variance2.044857917
MonotocityNot monotonic
2020-11-30T23:55:48.125573image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34736924.7%
 
23127516.3%
 
02937815.3%
 
1132266.9%
 
4120236.3%
 
571003.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02937815.3%
 
1132266.9%
 
23127516.3%
 
34736924.7%
 
4120236.3%
 
571003.7%
 
ValueCountFrequency (%) 
571003.7%
 
4120236.3%
 
34736924.7%
 
23127516.3%
 
1132266.9%
 
02937815.3%
 

KBA13_CCM_1400
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.871405062
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:48.204623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9330198213
Coefficient of variation (CV)0.3249349364
Kurtosis-0.07606242219
Mean2.871405062
Median Absolute Deviation (MAD)1
Skewness0.06731690585
Sum403062
Variance0.8705259869
MonotocityNot monotonic
2020-11-30T23:55:48.289004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36453533.7%
 
23521118.4%
 
42439812.7%
 
199235.2%
 
563043.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
199235.2%
 
23521118.4%
 
36453533.7%
 
42439812.7%
 
563043.3%
 
ValueCountFrequency (%) 
563043.3%
 
42439812.7%
 
36453533.7%
 
23521118.4%
 
199235.2%
 

KBA13_CCM_1401_2500
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.938641172
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:48.380056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9192150478
Coefficient of variation (CV)0.3128027527
Kurtosis-0.05514883027
Mean2.938641172
Median Absolute Deviation (MAD)1
Skewness-0.1158091681
Sum412500
Variance0.8449563042
MonotocityNot monotonic
2020-11-30T23:55:48.464461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36667734.8%
 
42928015.3%
 
22926715.3%
 
197305.1%
 
554172.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
197305.1%
 
22926715.3%
 
36667734.8%
 
42928015.3%
 
554172.8%
 
ValueCountFrequency (%) 
554172.8%
 
42928015.3%
 
36667734.8%
 
22926715.3%
 
197305.1%
 

KBA13_CCM_1500
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.578645162
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:48.555031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.397120322
Coefficient of variation (CV)0.5418040226
Kurtosis-1.431589977
Mean2.578645162
Median Absolute Deviation (MAD)1
Skewness0.1426798825
Sum361967
Variance1.951945193
MonotocityNot monotonic
2020-11-30T23:55:48.635850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
15126326.7%
 
43637519.0%
 
32749114.3%
 
2144937.6%
 
5107495.6%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
15126326.7%
 
2144937.6%
 
32749114.3%
 
43637519.0%
 
5107495.6%
 
ValueCountFrequency (%) 
5107495.6%
 
43637519.0%
 
32749114.3%
 
2144937.6%
 
15126326.7%
 

KBA13_CCM_1600
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.942758832
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:48.725759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9150225551
Coefficient of variation (CV)0.3109403819
Kurtosis-0.01856348084
Mean2.942758832
Median Absolute Deviation (MAD)1
Skewness0.09456611137
Sum413078
Variance0.8372662764
MonotocityNot monotonic
2020-11-30T23:55:48.809005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36622634.6%
 
23344917.5%
 
42608213.6%
 
174743.9%
 
571403.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
174743.9%
 
23344917.5%
 
36622634.6%
 
42608213.6%
 
571403.7%
 
ValueCountFrequency (%) 
571403.7%
 
42608213.6%
 
36622634.6%
 
23344917.5%
 
174743.9%
 

KBA13_CCM_1800
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.364590977
Minimum0
Maximum5
Zeros24878
Zeros (%)13.0%
Memory size1.5 MiB
2020-11-30T23:55:48.895004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.428590317
Coefficient of variation (CV)0.6041595907
Kurtosis-0.6169242322
Mean2.364590977
Median Absolute Deviation (MAD)1
Skewness-0.2320613574
Sum331920
Variance2.040870293
MonotocityNot monotonic
2020-11-30T23:55:48.976880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35053226.4%
 
23224416.8%
 
02487813.0%
 
4146217.6%
 
598145.1%
 
182824.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02487813.0%
 
182824.3%
 
23224416.8%
 
35053226.4%
 
4146217.6%
 
598145.1%
 
ValueCountFrequency (%) 
598145.1%
 
4146217.6%
 
35053226.4%
 
23224416.8%
 
182824.3%
 
02487813.0%
 

KBA13_CCM_2000
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.22919264
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:49.058349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9174303919
Coefficient of variation (CV)0.2841051911
Kurtosis-0.1395678488
Mean3.22919264
Median Absolute Deviation (MAD)1
Skewness0.03820628569
Sum453285
Variance0.8416785239
MonotocityNot monotonic
2020-11-30T23:55:49.141186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36493633.9%
 
43630718.9%
 
22243311.7%
 
5129226.7%
 
137732.0%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
137732.0%
 
22243311.7%
 
36493633.9%
 
43630718.9%
 
5129226.7%
 
ValueCountFrequency (%) 
5129226.7%
 
43630718.9%
 
36493633.9%
 
22243311.7%
 
137732.0%
 

KBA13_CCM_2500
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.693177366
Minimum0
Maximum5
Zeros15780
Zeros (%)8.2%
Memory size1.5 MiB
2020-11-30T23:55:49.227227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.44436976
Coefficient of variation (CV)0.5363069578
Kurtosis-0.5604463394
Mean2.693177366
Median Absolute Deviation (MAD)1
Skewness-0.3046412394
Sum378044
Variance2.086204003
MonotocityNot monotonic
2020-11-30T23:55:49.309703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35379028.1%
 
22094810.9%
 
4187759.8%
 
5171508.9%
 
0157808.2%
 
1139287.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
0157808.2%
 
1139287.3%
 
22094810.9%
 
35379028.1%
 
4187759.8%
 
5171508.9%
 
ValueCountFrequency (%) 
5171508.9%
 
4187759.8%
 
35379028.1%
 
22094810.9%
 
1139287.3%
 
0157808.2%
 

KBA13_CCM_2501
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.778608117
Minimum0
Maximum5
Zeros14392
Zeros (%)7.5%
Memory size1.5 MiB
2020-11-30T23:55:49.386874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.454250695
Coefficient of variation (CV)0.5233738022
Kurtosis-0.5527724243
Mean2.778608117
Median Absolute Deviation (MAD)1
Skewness-0.328632819
Sum390036
Variance2.114845084
MonotocityNot monotonic
2020-11-30T23:55:49.481319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35418928.3%
 
52006410.5%
 
4188879.9%
 
2187629.8%
 
0143927.5%
 
1140777.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
0143927.5%
 
1140777.3%
 
2187629.8%
 
35418928.3%
 
4188879.9%
 
52006410.5%
 
ValueCountFrequency (%) 
52006410.5%
 
4188879.9%
 
35418928.3%
 
2187629.8%
 
1140777.3%
 
0143927.5%
 

KBA13_CCM_3000
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.820589723
Minimum0
Maximum5
Zeros9117
Zeros (%)4.8%
Memory size1.5 MiB
2020-11-30T23:55:49.562285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.370008524
Coefficient of variation (CV)0.4857170517
Kurtosis-0.479093909
Mean2.820589723
Median Absolute Deviation (MAD)1
Skewness-0.2613188946
Sum395929
Variance1.876923357
MonotocityNot monotonic
2020-11-30T23:55:49.644346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35554529.0%
 
21957710.2%
 
41939210.1%
 
5189589.9%
 
1177829.3%
 
091174.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
091174.8%
 
1177829.3%
 
21957710.2%
 
35554529.0%
 
41939210.1%
 
5189589.9%
 
ValueCountFrequency (%) 
5189589.9%
 
41939210.1%
 
35554529.0%
 
21957710.2%
 
1177829.3%
 
091174.8%
 

KBA13_CCM_3001
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.871946485
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:49.724789image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.501274038
Coefficient of variation (CV)0.5227374696
Kurtosis-1.484350762
Mean2.871946485
Median Absolute Deviation (MAD)1
Skewness-0.1569084062
Sum403138
Variance2.253823738
MonotocityNot monotonic
2020-11-30T23:55:49.806005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
14950625.8%
 
44151421.7%
 
32954615.4%
 
51977610.3%
 
229< 0.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
14950625.8%
 
229< 0.1%
 
32954615.4%
 
44151421.7%
 
51977610.3%
 
ValueCountFrequency (%) 
51977610.3%
 
44151421.7%
 
32954615.4%
 
229< 0.1%
 
14950625.8%
 

KBA13_FAB_ASIEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.743344423
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:49.895538image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9473060889
Coefficient of variation (CV)0.3453106657
Kurtosis-0.0927661847
Mean2.743344423
Median Absolute Deviation (MAD)1
Skewness0.07979883952
Sum385086
Variance0.8973888262
MonotocityNot monotonic
2020-11-30T23:55:49.979067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36366733.2%
 
23764519.6%
 
41955610.2%
 
1142367.4%
 
552672.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1142367.4%
 
23764519.6%
 
36366733.2%
 
41955610.2%
 
552672.7%
 
ValueCountFrequency (%) 
552672.7%
 
41955610.2%
 
36366733.2%
 
23764519.6%
 
1142367.4%
 

KBA13_FAB_SONSTIGE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.803314075
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:50.081164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9411882279
Coefficient of variation (CV)0.3357412701
Kurtosis-0.02801934986
Mean2.803314075
Median Absolute Deviation (MAD)1
Skewness0.06367267959
Sum393504
Variance0.8858352803
MonotocityNot monotonic
2020-11-30T23:55:50.174041image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36579334.3%
 
23533118.4%
 
42084810.9%
 
1124816.5%
 
559183.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1124816.5%
 
23533118.4%
 
36579334.3%
 
42084810.9%
 
559183.1%
 
ValueCountFrequency (%) 
559183.1%
 
42084810.9%
 
36579334.3%
 
23533118.4%
 
1124816.5%
 

KBA13_FIAT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.242671207
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:50.273723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9577289634
Coefficient of variation (CV)0.2953518573
Kurtosis-0.238769618
Mean3.242671207
Median Absolute Deviation (MAD)1
Skewness0.03783642701
Sum455177
Variance0.9172447674
MonotocityNot monotonic
2020-11-30T23:55:50.370477image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36324633.0%
 
43455518.0%
 
22260511.8%
 
5155118.1%
 
144542.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
144542.3%
 
22260511.8%
 
36324633.0%
 
43455518.0%
 
5155118.1%
 
ValueCountFrequency (%) 
5155118.1%
 
43455518.0%
 
36324633.0%
 
22260511.8%
 
144542.3%
 

KBA13_FORD
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.856922014
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:50.466369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.07214441
Coefficient of variation (CV)0.3752795509
Kurtosis-0.4083927435
Mean2.856922014
Median Absolute Deviation (MAD)1
Skewness0.1342711727
Sum401029
Variance1.149493636
MonotocityNot monotonic
2020-11-30T23:55:50.549564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35690029.7%
 
23392517.7%
 
42262711.8%
 
1156568.2%
 
5112635.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1156568.2%
 
23392517.7%
 
35690029.7%
 
42262711.8%
 
5112635.9%
 
ValueCountFrequency (%) 
5112635.9%
 
42262711.8%
 
35690029.7%
 
23392517.7%
 
1156568.2%
 

KBA13_GBZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.663477499
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:50.644918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.014805797
Coefficient of variation (CV)0.2770061498
Kurtosis-0.4859239634
Mean3.663477499
Median Absolute Deviation (MAD)1
Skewness-0.2833215973
Sum514246
Variance1.029830805
MonotocityNot monotonic
2020-11-30T23:55:50.727660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35067726.4%
 
43963220.7%
 
53561218.6%
 
2111775.8%
 
132731.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
132731.7%
 
2111775.8%
 
35067726.4%
 
43963220.7%
 
53561218.6%
 
ValueCountFrequency (%) 
53561218.6%
 
43963220.7%
 
35067726.4%
 
2111775.8%
 
132731.7%
 

KBA13_HALTER_20
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.770536649
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:50.815736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9235390141
Coefficient of variation (CV)0.3333430057
Kurtosis-0.02894363981
Mean2.770536649
Median Absolute Deviation (MAD)1
Skewness0.09597124385
Sum388903
Variance0.8529243106
MonotocityNot monotonic
2020-11-30T23:55:50.898882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36444133.6%
 
23865720.2%
 
42021110.5%
 
1119726.2%
 
550902.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1119726.2%
 
23865720.2%
 
36444133.6%
 
42021110.5%
 
550902.7%
 
ValueCountFrequency (%) 
550902.7%
 
42021110.5%
 
36444133.6%
 
23865720.2%
 
1119726.2%
 

KBA13_HALTER_25
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.615540247
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:50.989031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9319086888
Coefficient of variation (CV)0.3562968262
Kurtosis-0.1403309317
Mean2.615540247
Median Absolute Deviation (MAD)1
Skewness0.02993208687
Sum367146
Variance0.8684538043
MonotocityNot monotonic
2020-11-30T23:55:51.073107image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36422833.5%
 
23876820.2%
 
1186869.7%
 
4152057.9%
 
534841.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1186869.7%
 
23876820.2%
 
36422833.5%
 
4152057.9%
 
534841.8%
 
ValueCountFrequency (%) 
534841.8%
 
4152057.9%
 
36422833.5%
 
23876820.2%
 
1186869.7%
 

KBA13_HALTER_30
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.749727508
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:51.163688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.010695377
Coefficient of variation (CV)0.3675620125
Kurtosis-0.185727734
Mean2.749727508
Median Absolute Deviation (MAD)1
Skewness0.140382087
Sum385982
Variance1.021505144
MonotocityNot monotonic
2020-11-30T23:55:51.246536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36171432.2%
 
23557618.6%
 
4185739.7%
 
1167868.8%
 
577224.0%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1167868.8%
 
23557618.6%
 
36171432.2%
 
4185739.7%
 
577224.0%
 
ValueCountFrequency (%) 
577224.0%
 
4185739.7%
 
36171432.2%
 
23557618.6%
 
1167868.8%
 

KBA13_HALTER_35
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.91888638
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:51.339513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.069563239
Coefficient of variation (CV)0.3664285278
Kurtosis-0.4443085524
Mean2.91888638
Median Absolute Deviation (MAD)1
Skewness0.04266879156
Sum409727
Variance1.143965522
MonotocityNot monotonic
2020-11-30T23:55:51.425199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35685129.7%
 
23105016.2%
 
42647613.8%
 
1147007.7%
 
5112945.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1147007.7%
 
23105016.2%
 
35685129.7%
 
42647613.8%
 
5112945.9%
 
ValueCountFrequency (%) 
5112945.9%
 
42647613.8%
 
35685129.7%
 
23105016.2%
 
1147007.7%
 

KBA13_HALTER_40
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.027698029
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:51.515981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.024388467
Coefficient of variation (CV)0.3383390476
Kurtosis-0.3086826458
Mean3.027698029
Median Absolute Deviation (MAD)1
Skewness0.007258454748
Sum425001
Variance1.049371732
MonotocityNot monotonic
2020-11-30T23:55:51.599134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36031031.5%
 
42917515.2%
 
22843714.8%
 
5120126.3%
 
1104375.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1104375.4%
 
22843714.8%
 
36031031.5%
 
42917515.2%
 
5120126.3%
 
ValueCountFrequency (%) 
5120126.3%
 
42917515.2%
 
36031031.5%
 
22843714.8%
 
1104375.4%
 

KBA13_HALTER_45
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.090047089
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:51.689661image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.010755738
Coefficient of variation (CV)0.3271004321
Kurtosis-0.2858946393
Mean3.090047089
Median Absolute Deviation (MAD)1
Skewness-0.0001263722988
Sum433753
Variance1.021627162
MonotocityNot monotonic
2020-11-30T23:55:51.772449image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36084331.7%
 
43088416.1%
 
22697214.1%
 
5130186.8%
 
186544.5%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
186544.5%
 
22697214.1%
 
36084331.7%
 
43088416.1%
 
5130186.8%
 
ValueCountFrequency (%) 
5130186.8%
 
43088416.1%
 
36084331.7%
 
22697214.1%
 
186544.5%
 

KBA13_HALTER_50
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.902130782
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:51.862004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.023940375
Coefficient of variation (CV)0.3528236498
Kurtosis-0.3223824964
Mean2.902130782
Median Absolute Deviation (MAD)1
Skewness0.06004445286
Sum407375
Variance1.048453891
MonotocityNot monotonic
2020-11-30T23:55:51.943739image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35924730.9%
 
23277317.1%
 
42588713.5%
 
1129456.8%
 
595195.0%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1129456.8%
 
23277317.1%
 
35924730.9%
 
42588713.5%
 
595195.0%
 
ValueCountFrequency (%) 
595195.0%
 
42588713.5%
 
35924730.9%
 
23277317.1%
 
1129456.8%
 

KBA13_HALTER_55
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.983593477
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:52.035994image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.030085356
Coefficient of variation (CV)0.3452499022
Kurtosis-0.3305388282
Mean2.983593477
Median Absolute Deviation (MAD)1
Skewness0.05139118664
Sum418810
Variance1.061075841
MonotocityNot monotonic
2020-11-30T23:55:52.118059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35954431.1%
 
23068216.0%
 
42742714.3%
 
5115976.1%
 
1111215.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1111215.8%
 
23068216.0%
 
35954431.1%
 
42742714.3%
 
5115976.1%
 
ValueCountFrequency (%) 
5115976.1%
 
42742714.3%
 
35954431.1%
 
23068216.0%
 
1111215.8%
 

KBA13_HALTER_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.985203496
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:52.207829image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.021825888
Coefficient of variation (CV)0.342296895
Kurtosis-0.2994671537
Mean2.985203496
Median Absolute Deviation (MAD)1
Skewness0.03534544924
Sum419036
Variance1.044128145
MonotocityNot monotonic
2020-11-30T23:55:52.292460image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36041231.5%
 
23005615.7%
 
42769114.4%
 
5111785.8%
 
1110345.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1110345.8%
 
23005615.7%
 
36041231.5%
 
42769114.4%
 
5111785.8%
 
ValueCountFrequency (%) 
5111785.8%
 
42769114.4%
 
36041231.5%
 
23005615.7%
 
1110345.8%
 

KBA13_HALTER_65
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.33614493
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:52.396214image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.961205169
Coefficient of variation (CV)0.2881185288
Kurtosis-0.2615610691
Mean3.33614493
Median Absolute Deviation (MAD)1
Skewness-0.02309140673
Sum468298
Variance0.923915377
MonotocityNot monotonic
2020-11-30T23:55:52.482655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36192432.3%
 
43729019.5%
 
2187899.8%
 
5183559.6%
 
140132.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
140132.1%
 
2187899.8%
 
36192432.3%
 
43729019.5%
 
5183559.6%
 
ValueCountFrequency (%) 
5183559.6%
 
43729019.5%
 
36192432.3%
 
2187899.8%
 
140132.1%
 

KBA13_HALTER_66
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.225709014
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:52.574951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.049287139
Coefficient of variation (CV)0.3252888387
Kurtosis-0.4473664861
Mean3.225709014
Median Absolute Deviation (MAD)1
Skewness-0.04387944598
Sum452796
Variance1.1010035
MonotocityNot monotonic
2020-11-30T23:55:52.657061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35712829.8%
 
43314317.3%
 
22394812.5%
 
5186989.8%
 
174543.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
174543.9%
 
22394812.5%
 
35712829.8%
 
43314317.3%
 
5186989.8%
 
ValueCountFrequency (%) 
5186989.8%
 
43314317.3%
 
35712829.8%
 
22394812.5%
 
174543.9%
 

KBA13_HERST_ASIEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.760028781
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:52.746554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.953098192
Coefficient of variation (CV)0.3453218309
Kurtosis-0.1393643316
Mean2.760028781
Median Absolute Deviation (MAD)1
Skewness0.05221876741
Sum387428
Variance0.9083961636
MonotocityNot monotonic
2020-11-30T23:55:52.829689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36332133.0%
 
23665919.1%
 
42087610.9%
 
1142337.4%
 
552822.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1142337.4%
 
23665919.1%
 
36332133.0%
 
42087610.9%
 
552822.8%
 
ValueCountFrequency (%) 
552822.8%
 
42087610.9%
 
36332133.0%
 
23665919.1%
 
1142337.4%
 

KBA13_HERST_AUDI_VW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.055538537
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:52.921492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9741951651
Coefficient of variation (CV)0.3188292844
Kurtosis-0.1327134235
Mean3.055538537
Median Absolute Deviation (MAD)1
Skewness-0.02459877161
Sum428909
Variance0.9490562197
MonotocityNot monotonic
2020-11-30T23:55:53.005298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36437333.6%
 
43041615.9%
 
22636413.8%
 
5105455.5%
 
186734.5%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
186734.5%
 
22636413.8%
 
36437333.6%
 
43041615.9%
 
5105455.5%
 
ValueCountFrequency (%) 
5105455.5%
 
43041615.9%
 
36437333.6%
 
22636413.8%
 
186734.5%
 

KBA13_HERST_BMW_BENZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.495636563
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:53.095257image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9381077471
Coefficient of variation (CV)0.268365355
Kurtosis-0.3119666781
Mean3.495636563
Median Absolute Deviation (MAD)1
Skewness-0.05682404457
Sum490686
Variance0.8800461452
MonotocityNot monotonic
2020-11-30T23:55:53.177944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36028131.5%
 
44107521.4%
 
52337212.2%
 
2130406.8%
 
126031.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
126031.4%
 
2130406.8%
 
36028131.5%
 
44107521.4%
 
52337212.2%
 
ValueCountFrequency (%) 
52337212.2%
 
44107521.4%
 
36028131.5%
 
2130406.8%
 
126031.4%
 

KBA13_HERST_EUROPA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.049525899
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:53.267892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.02890371
Coefficient of variation (CV)0.3373979246
Kurtosis-0.3254315097
Mean3.049525899
Median Absolute Deviation (MAD)1
Skewness0.033984511
Sum428065
Variance1.058642844
MonotocityNot monotonic
2020-11-30T23:55:53.351130image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36017931.4%
 
42872315.0%
 
22855114.9%
 
5131546.9%
 
197645.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
197645.1%
 
22855114.9%
 
36017931.4%
 
42872315.0%
 
5131546.9%
 
ValueCountFrequency (%) 
5131546.9%
 
42872315.0%
 
36017931.4%
 
22855114.9%
 
197645.1%
 

KBA13_HERST_FORD_OPEL
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.812959942
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:53.441834image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.095075219
Coefficient of variation (CV)0.3892964145
Kurtosis-0.5149300236
Mean2.812959942
Median Absolute Deviation (MAD)1
Skewness0.1068780573
Sum394858
Variance1.199189736
MonotocityNot monotonic
2020-11-30T23:55:53.524179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35441828.4%
 
23332017.4%
 
42353712.3%
 
1186669.7%
 
5104305.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1186669.7%
 
23332017.4%
 
35441828.4%
 
42353712.3%
 
5104305.4%
 
ValueCountFrequency (%) 
5104305.4%
 
42353712.3%
 
35441828.4%
 
23332017.4%
 
1186669.7%
 

KBA13_HERST_SONST
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.803314075
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:53.613711image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9411882279
Coefficient of variation (CV)0.3357412701
Kurtosis-0.02801934986
Mean2.803314075
Median Absolute Deviation (MAD)1
Skewness0.06367267959
Sum393504
Variance0.8858352803
MonotocityNot monotonic
2020-11-30T23:55:53.696220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36579334.3%
 
23533118.4%
 
42084810.9%
 
1124816.5%
 
559183.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1124816.5%
 
23533118.4%
 
36579334.3%
 
42084810.9%
 
559183.1%
 
ValueCountFrequency (%) 
559183.1%
 
42084810.9%
 
36579334.3%
 
23533118.4%
 
1124816.5%
 

KBA13_HHZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.595429255
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:53.786295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9357291255
Coefficient of variation (CV)0.2602551904
Kurtosis-0.6346260022
Mean3.595429255
Median Absolute Deviation (MAD)1
Skewness0.03309650049
Sum504694
Variance0.8755889963
MonotocityNot monotonic
2020-11-30T23:55:53.868654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36020631.4%
 
43822119.9%
 
52953515.4%
 
2111085.8%
 
113010.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
113010.7%
 
2111085.8%
 
36020631.4%
 
43822119.9%
 
52953515.4%
 
ValueCountFrequency (%) 
52953515.4%
 
43822119.9%
 
36020631.4%
 
2111085.8%
 
113010.7%
 

KBA13_KMH_0_140
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.188699945
Minimum0
Maximum5
Zeros21541
Zeros (%)11.2%
Memory size1.5 MiB
2020-11-30T23:55:53.958705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.524134908
Coefficient of variation (CV)0.6963653979
Kurtosis-1.148299836
Mean2.188699945
Median Absolute Deviation (MAD)2
Skewness0.09855194772
Sum307230
Variance2.322987218
MonotocityNot monotonic
2020-11-30T23:55:54.041124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34993126.1%
 
14168021.7%
 
02154111.2%
 
4153288.0%
 
5102215.3%
 
216700.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02154111.2%
 
14168021.7%
 
216700.9%
 
34993126.1%
 
4153288.0%
 
5102215.3%
 
ValueCountFrequency (%) 
5102215.3%
 
4153288.0%
 
34993126.1%
 
216700.9%
 
14168021.7%
 
02154111.2%
 

KBA13_KMH_110
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
1
114895 
3
14232 
2
 
11244
ValueCountFrequency (%) 
111489559.9%
 
3142327.4%
 
2112445.9%
 
(Missing)5128126.8%
 
2020-11-30T23:55:54.135542image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
111489520.0%
 
n10256217.8%
 
a512818.9%
 
3142322.5%
 
2112442.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014037150.0%
 
111489540.9%
 
3142325.1%
 
2112444.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
.14037133.3%
 
014037133.3%
 
111489527.3%
 
3142323.4%
 
2112442.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
111489520.0%
 
n10256217.8%
 
a512818.9%
 
3142322.5%
 
2112442.0%
 

KBA13_KMH_140
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.638479458
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:54.221363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.351952662
Coefficient of variation (CV)0.5123984034
Kurtosis-1.326060439
Mean2.638479458
Median Absolute Deviation (MAD)1
Skewness0.111716822
Sum370366
Variance1.827776
MonotocityNot monotonic
2020-11-30T23:55:54.302197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
14368422.8%
 
43504418.3%
 
32986615.6%
 
22065910.8%
 
5111185.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
14368422.8%
 
22065910.8%
 
32986615.6%
 
43504418.3%
 
5111185.8%
 
ValueCountFrequency (%) 
5111185.8%
 
43504418.3%
 
32986615.6%
 
22065910.8%
 
14368422.8%
 

KBA13_KMH_140_210
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.678836797
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:54.389324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.981038876
Coefficient of variation (CV)0.3662182322
Kurtosis-0.2581183473
Mean2.678836797
Median Absolute Deviation (MAD)1
Skewness0.04683244594
Sum376031
Variance0.9624372763
MonotocityNot monotonic
2020-11-30T23:55:54.473987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36180832.3%
 
23606618.8%
 
4188269.8%
 
1187969.8%
 
548752.5%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1187969.8%
 
23606618.8%
 
36180832.3%
 
4188269.8%
 
548752.5%
 
ValueCountFrequency (%) 
548752.5%
 
4188269.8%
 
36180832.3%
 
23606618.8%
 
1187969.8%
 

KBA13_KMH_180
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.730385906
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:54.564447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9717099197
Coefficient of variation (CV)0.3558873922
Kurtosis-0.2505712569
Mean2.730385906
Median Absolute Deviation (MAD)1
Skewness0.02339643342
Sum383267
Variance0.9442201681
MonotocityNot monotonic
2020-11-30T23:55:54.646990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36178532.2%
 
23600718.8%
 
42119311.1%
 
1164518.6%
 
549352.6%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1164518.6%
 
23600718.8%
 
36178532.2%
 
42119311.1%
 
549352.6%
 
ValueCountFrequency (%) 
549352.6%
 
42119311.1%
 
36178532.2%
 
23600718.8%
 
1164518.6%
 

KBA13_KMH_210
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.138055581
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:54.738046image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9268217252
Coefficient of variation (CV)0.2953490469
Kurtosis-0.05302073774
Mean3.138055581
Median Absolute Deviation (MAD)1
Skewness0.006016949612
Sum440492
Variance0.8589985103
MonotocityNot monotonic
2020-11-30T23:55:54.820506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36616534.5%
 
43335117.4%
 
22450612.8%
 
5108085.6%
 
155412.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
155412.9%
 
22450612.8%
 
36616534.5%
 
43335117.4%
 
5108085.6%
 
ValueCountFrequency (%) 
5108085.6%
 
43335117.4%
 
36616534.5%
 
22450612.8%
 
155412.9%
 

KBA13_KMH_211
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.745481617
Minimum0
Maximum5
Zeros20007
Zeros (%)10.4%
Memory size1.5 MiB
2020-11-30T23:55:54.906519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.510259898
Coefficient of variation (CV)0.5500892407
Kurtosis-0.5625299899
Mean2.745481617
Median Absolute Deviation (MAD)1
Skewness-0.3802347973
Sum385386
Variance2.280884959
MonotocityNot monotonic
2020-11-30T23:55:54.990074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35177027.0%
 
22292612.0%
 
52053910.7%
 
02000710.4%
 
4188009.8%
 
163293.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02000710.4%
 
163293.3%
 
22292612.0%
 
35177027.0%
 
4188009.8%
 
52053910.7%
 
ValueCountFrequency (%) 
52053910.7%
 
4188009.8%
 
35177027.0%
 
22292612.0%
 
163293.3%
 
02000710.4%
 

KBA13_KMH_250
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.739119904
Minimum0
Maximum5
Zeros20125
Zeros (%)10.5%
Memory size1.5 MiB
2020-11-30T23:55:55.066317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.509620005
Coefficient of variation (CV)0.551133232
Kurtosis-0.5625984589
Mean2.739119904
Median Absolute Deviation (MAD)1
Skewness-0.3786828138
Sum384493
Variance2.27895256
MonotocityNot monotonic
2020-11-30T23:55:55.147545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35206327.2%
 
22283911.9%
 
52034810.6%
 
02012510.5%
 
4186309.7%
 
163663.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02012510.5%
 
163663.3%
 
22283911.9%
 
35206327.2%
 
4186309.7%
 
52034810.6%
 
ValueCountFrequency (%) 
52034810.6%
 
4186309.7%
 
35206327.2%
 
22283911.9%
 
163663.3%
 
02012510.5%
 

KBA13_KMH_251
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
1
115323 
3
22793 
2
 
2255
ValueCountFrequency (%) 
111532360.2%
 
32279311.9%
 
222551.2%
 
(Missing)5128126.8%
 
2020-11-30T23:55:55.243263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
111532320.1%
 
n10256217.8%
 
a512818.9%
 
3227934.0%
 
222550.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014037150.0%
 
111532341.1%
 
3227938.1%
 
222550.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
.14037133.3%
 
014037133.3%
 
111532327.4%
 
3227935.4%
 
222550.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
111532320.1%
 
n10256217.8%
 
a512818.9%
 
3227934.0%
 
222550.4%
 

KBA13_KRSAQUOT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.996430887
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:55.333466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9955132367
Coefficient of variation (CV)0.3322330047
Kurtosis-0.2152403592
Mean2.996430887
Median Absolute Deviation (MAD)1
Skewness0.0265045596
Sum420612
Variance0.9910466045
MonotocityNot monotonic
2020-11-30T23:55:55.415905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36244732.6%
 
22946115.4%
 
42806614.6%
 
5104225.4%
 
199755.2%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
199755.2%
 
22946115.4%
 
36244732.6%
 
42806614.6%
 
5104225.4%
 
ValueCountFrequency (%) 
5104225.4%
 
42806614.6%
 
36244732.6%
 
22946115.4%
 
199755.2%
 

KBA13_KRSHERST_AUDI_VW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.08714763
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:55.506415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9830396275
Coefficient of variation (CV)0.3184297433
Kurtosis-0.2244924188
Mean3.08714763
Median Absolute Deviation (MAD)1
Skewness-0.05720705267
Sum433346
Variance0.9663669092
MonotocityNot monotonic
2020-11-30T23:55:55.588425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36131632.0%
 
43341817.4%
 
22641713.8%
 
5109185.7%
 
183024.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
183024.3%
 
22641713.8%
 
36131632.0%
 
43341817.4%
 
5109185.7%
 
ValueCountFrequency (%) 
5109185.7%
 
43341817.4%
 
36131632.0%
 
22641713.8%
 
183024.3%
 

KBA13_KRSHERST_BMW_BENZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.268267662
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:55.678685image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9496509321
Coefficient of variation (CV)0.2905670619
Kurtosis-0.216228949
Mean3.268267662
Median Absolute Deviation (MAD)1
Skewness0.04054579156
Sum458770
Variance0.9018368928
MonotocityNot monotonic
2020-11-30T23:55:55.763029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36411033.5%
 
43491918.2%
 
22119811.1%
 
5160568.4%
 
140882.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
140882.1%
 
22119811.1%
 
36411033.5%
 
43491918.2%
 
5160568.4%
 
ValueCountFrequency (%) 
5160568.4%
 
43491918.2%
 
36411033.5%
 
22119811.1%
 
140882.1%
 

KBA13_KRSHERST_FORD_OPEL
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.826673601
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:55.854059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.058524557
Coefficient of variation (CV)0.3744771086
Kurtosis-0.4305283661
Mean2.826673601
Median Absolute Deviation (MAD)1
Skewness0.06444939915
Sum396783
Variance1.120474237
MonotocityNot monotonic
2020-11-30T23:55:55.937921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35696029.7%
 
23294717.2%
 
42443512.7%
 
1169698.9%
 
590604.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1169698.9%
 
23294717.2%
 
35696029.7%
 
42443512.7%
 
590604.7%
 
ValueCountFrequency (%) 
590604.7%
 
42443512.7%
 
35696029.7%
 
23294717.2%
 
1169698.9%
 

KBA13_KRSSEG_KLEIN
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
2
129376 
1
 
7132
3
 
3863
ValueCountFrequency (%) 
212937667.5%
 
171323.7%
 
338632.0%
 
(Missing)5128126.8%
 
2020-11-30T23:55:56.041808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
212937622.5%
 
n10256217.8%
 
a512818.9%
 
171321.2%
 
338630.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014037150.0%
 
212937646.1%
 
171322.5%
 
338631.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
.14037133.3%
 
014037133.3%
 
212937630.7%
 
171321.7%
 
338630.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
212937622.5%
 
n10256217.8%
 
a512818.9%
 
171321.2%
 
338630.7%
 

KBA13_KRSSEG_OBER
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
2
99651 
3
22142 
1
18551 
0
 
27
ValueCountFrequency (%) 
29965152.0%
 
32214211.6%
 
1185519.7%
 
027< 0.1%
 
(Missing)5128126.8%
 
2020-11-30T23:55:56.140774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
014039824.4%
 
.14037124.4%
 
n10256217.8%
 
29965117.3%
 
a512818.9%
 
3221423.9%
 
1185513.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014039850.0%
 
29965135.5%
 
3221427.9%
 
1185516.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
014039833.3%
 
.14037133.3%
 
29965123.7%
 
3221425.3%
 
1185514.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
014039824.4%
 
.14037124.4%
 
n10256217.8%
 
29965117.3%
 
a512818.9%
 
3221423.9%
 
1185513.2%
 

KBA13_KRSSEG_VAN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
2
91432 
1
25726 
3
23153 
0
 
60
ValueCountFrequency (%) 
29143247.7%
 
12572613.4%
 
32315312.1%
 
060< 0.1%
 
(Missing)5128126.8%
 
2020-11-30T23:55:56.235792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
014043124.4%
 
.14037124.4%
 
n10256217.8%
 
29143215.9%
 
a512818.9%
 
1257264.5%
 
3231534.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014043150.0%
 
29143232.6%
 
1257269.2%
 
3231538.2%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
014043133.3%
 
.14037133.3%
 
29143221.7%
 
1257266.1%
 
3231535.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
014043124.4%
 
.14037124.4%
 
n10256217.8%
 
29143215.9%
 
a512818.9%
 
1257264.5%
 
3231534.0%
 

KBA13_KRSZUL_NEU
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
2
71560 
3
35741 
1
30394 
0
 
2676
ValueCountFrequency (%) 
27156037.3%
 
33574118.6%
 
13039415.9%
 
026761.4%
 
(Missing)5128126.8%
 
2020-11-30T23:55:56.339217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
014304724.9%
 
.14037124.4%
 
n10256217.8%
 
27156012.4%
 
a512818.9%
 
3357416.2%
 
1303945.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014304751.0%
 
27156025.5%
 
33574112.7%
 
13039410.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
014304734.0%
 
.14037133.3%
 
27156017.0%
 
3357418.5%
 
1303947.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
014304724.9%
 
.14037124.4%
 
n10256217.8%
 
27156012.4%
 
a512818.9%
 
3357416.2%
 
1303945.3%
 

KBA13_KW_0_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.767651438
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:56.430008image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9549701696
Coefficient of variation (CV)0.3450471243
Kurtosis-0.1642491798
Mean2.767651438
Median Absolute Deviation (MAD)1
Skewness0.02986273748
Sum388498
Variance0.9119680249
MonotocityNot monotonic
2020-11-30T23:55:56.512628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36326533.0%
 
23599218.8%
 
42161911.3%
 
1143087.5%
 
551872.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1143087.5%
 
23599218.8%
 
36326533.0%
 
42161911.3%
 
551872.7%
 
ValueCountFrequency (%) 
551872.7%
 
42161911.3%
 
36326533.0%
 
23599218.8%
 
1143087.5%
 

KBA13_KW_110
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.60707696
Minimum0
Maximum5
Zeros19148
Zeros (%)10.0%
Memory size1.5 MiB
2020-11-30T23:55:56.599444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.425965787
Coefficient of variation (CV)0.5469596061
Kurtosis-0.4586967915
Mean2.60707696
Median Absolute Deviation (MAD)1
Skewness-0.332508155
Sum365958
Variance2.033378427
MonotocityNot monotonic
2020-11-30T23:55:56.682606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35385328.1%
 
22704314.1%
 
01914810.0%
 
4178629.3%
 
5141007.4%
 
183654.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
01914810.0%
 
183654.4%
 
22704314.1%
 
35385328.1%
 
4178629.3%
 
5141007.4%
 
ValueCountFrequency (%) 
5141007.4%
 
4178629.3%
 
35385328.1%
 
22704314.1%
 
183654.4%
 
01914810.0%
 

KBA13_KW_120
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.508488221
Minimum0
Maximum5
Zeros17157
Zeros (%)9.0%
Memory size1.5 MiB
2020-11-30T23:55:56.759238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.554176205
Coefficient of variation (CV)0.619566874
Kurtosis-1.075043311
Mean2.508488221
Median Absolute Deviation (MAD)1
Skewness-0.1121705976
Sum352119
Variance2.415463677
MonotocityNot monotonic
2020-11-30T23:55:56.841013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35067926.4%
 
13225116.8%
 
4189979.9%
 
0171579.0%
 
5164238.6%
 
248642.5%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
0171579.0%
 
13225116.8%
 
248642.5%
 
35067926.4%
 
4189979.9%
 
5164238.6%
 
ValueCountFrequency (%) 
5164238.6%
 
4189979.9%
 
35067926.4%
 
248642.5%
 
13225116.8%
 
0171579.0%
 

KBA13_KW_121
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.775751402
Minimum0
Maximum5
Zeros15218
Zeros (%)7.9%
Memory size1.5 MiB
2020-11-30T23:55:56.920096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.474827616
Coefficient of variation (CV)0.5313255413
Kurtosis-0.600056625
Mean2.775751402
Median Absolute Deviation (MAD)1
Skewness-0.326024788
Sum389635
Variance2.175116497
MonotocityNot monotonic
2020-11-30T23:55:57.001510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35220627.2%
 
52065510.8%
 
21946010.2%
 
41933010.1%
 
0152187.9%
 
1135027.0%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
0152187.9%
 
1135027.0%
 
21946010.2%
 
35220627.2%
 
41933010.1%
 
52065510.8%
 
ValueCountFrequency (%) 
52065510.8%
 
41933010.1%
 
35220627.2%
 
21946010.2%
 
1135027.0%
 
0152187.9%
 

KBA13_KW_30
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
1
102600 
2
24871 
3
12900 
ValueCountFrequency (%) 
110260053.5%
 
22487113.0%
 
3129006.7%
 
(Missing)5128126.8%
 
2020-11-30T23:55:57.094094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
110260017.8%
 
n10256217.8%
 
a512818.9%
 
2248714.3%
 
3129002.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014037150.0%
 
110260036.5%
 
2248718.9%
 
3129004.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
.14037133.3%
 
014037133.3%
 
110260024.4%
 
2248715.9%
 
3129003.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
110260017.8%
 
n10256217.8%
 
a512818.9%
 
2248714.3%
 
3129002.2%
 

KBA13_KW_40
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.190943998
Minimum0
Maximum5
Zeros19498
Zeros (%)10.2%
Memory size1.5 MiB
2020-11-30T23:55:57.173662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.36030058
Coefficient of variation (CV)0.6208741898
Kurtosis-0.7316513023
Mean2.190943998
Median Absolute Deviation (MAD)1
Skewness-0.001832317544
Sum307545
Variance1.850417668
MonotocityNot monotonic
2020-11-30T23:55:57.254937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34900625.6%
 
12770514.5%
 
22544013.3%
 
01949810.2%
 
4116686.1%
 
570543.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
01949810.2%
 
12770514.5%
 
22544013.3%
 
34900625.6%
 
4116686.1%
 
570543.7%
 
ValueCountFrequency (%) 
570543.7%
 
4116686.1%
 
34900625.6%
 
22544013.3%
 
12770514.5%
 
01949810.2%
 

KBA13_KW_50
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.170369948
Minimum0
Maximum5
Zeros29204
Zeros (%)15.2%
Memory size1.5 MiB
2020-11-30T23:55:57.332140image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.412521485
Coefficient of variation (CV)0.6508206061
Kurtosis-0.7098842924
Mean2.170369948
Median Absolute Deviation (MAD)1
Skewness-0.1319295587
Sum304657
Variance1.995216946
MonotocityNot monotonic
2020-11-30T23:55:57.413001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34647424.2%
 
23656719.1%
 
02920415.2%
 
4117416.1%
 
191974.8%
 
571883.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02920415.2%
 
191974.8%
 
23656719.1%
 
34647424.2%
 
4117416.1%
 
571883.8%
 
ValueCountFrequency (%) 
571883.8%
 
4117416.1%
 
34647424.2%
 
23656719.1%
 
191974.8%
 
02920415.2%
 

KBA13_KW_60
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.165062584
Minimum0
Maximum5
Zeros24799
Zeros (%)12.9%
Memory size1.5 MiB
2020-11-30T23:55:57.488465image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.380791861
Coefficient of variation (CV)0.6377607149
Kurtosis-0.6772409111
Mean2.165062584
Median Absolute Deviation (MAD)1
Skewness-0.05280492599
Sum303912
Variance1.906586165
MonotocityNot monotonic
2020-11-30T23:55:57.569197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34502223.5%
 
23485418.2%
 
02479912.9%
 
1168908.8%
 
4117826.1%
 
570243.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02479912.9%
 
1168908.8%
 
23485418.2%
 
34502223.5%
 
4117826.1%
 
570243.7%
 
ValueCountFrequency (%) 
570243.7%
 
4117826.1%
 
34502223.5%
 
23485418.2%
 
1168908.8%
 
02479912.9%
 

KBA13_KW_61_120
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.084867957
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:57.650996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9230644239
Coefficient of variation (CV)0.2992233174
Kurtosis-0.01166976236
Mean3.084867957
Median Absolute Deviation (MAD)1
Skewness-0.01929304727
Sum433026
Variance0.8520479307
MonotocityNot monotonic
2020-11-30T23:55:57.737928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36684934.9%
 
43212016.8%
 
22570513.4%
 
592234.8%
 
164743.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
164743.4%
 
22570513.4%
 
36684934.9%
 
43212016.8%
 
592234.8%
 
ValueCountFrequency (%) 
592234.8%
 
43212016.8%
 
36684934.9%
 
22570513.4%
 
164743.4%
 

KBA13_KW_70
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.255230781
Minimum0
Maximum5
Zeros27083
Zeros (%)14.1%
Memory size1.5 MiB
2020-11-30T23:55:57.825589image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.415182554
Coefficient of variation (CV)0.627511191
Kurtosis-0.6695676825
Mean2.255230781
Median Absolute Deviation (MAD)1
Skewness-0.1849097869
Sum316569
Variance2.00274166
MonotocityNot monotonic
2020-11-30T23:55:57.910077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34831125.2%
 
23490318.2%
 
02708314.1%
 
4133207.0%
 
188054.6%
 
579494.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02708314.1%
 
188054.6%
 
23490318.2%
 
34831125.2%
 
4133207.0%
 
579494.1%
 
ValueCountFrequency (%) 
579494.1%
 
4133207.0%
 
34831125.2%
 
23490318.2%
 
188054.6%
 
02708314.1%
 

KBA13_KW_80
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.269941797
Minimum0
Maximum5
Zeros23396
Zeros (%)12.2%
Memory size1.5 MiB
2020-11-30T23:55:57.987505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.389211747
Coefficient of variation (CV)0.6120032456
Kurtosis-0.6372520249
Mean2.269941797
Median Absolute Deviation (MAD)1
Skewness-0.141427404
Sum318634
Variance1.929909279
MonotocityNot monotonic
2020-11-30T23:55:58.070035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34848525.3%
 
23308317.3%
 
02339612.2%
 
1142097.4%
 
4131866.9%
 
580124.2%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02339612.2%
 
1142097.4%
 
23308317.3%
 
34848525.3%
 
4131866.9%
 
580124.2%
 
ValueCountFrequency (%) 
580124.2%
 
4131866.9%
 
34848525.3%
 
23308317.3%
 
1142097.4%
 
02339612.2%
 

KBA13_KW_90
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.423349552
Minimum0
Maximum5
Zeros23538
Zeros (%)12.3%
Memory size1.5 MiB
2020-11-30T23:55:58.147178image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.429510243
Coefficient of variation (CV)0.5898902373
Kurtosis-0.5724649255
Mean2.423349552
Median Absolute Deviation (MAD)1
Skewness-0.2540340996
Sum340168
Variance2.043499533
MonotocityNot monotonic
2020-11-30T23:55:58.229313image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35084126.5%
 
23197116.7%
 
02353812.3%
 
4154588.1%
 
5108275.6%
 
177364.0%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
02353812.3%
 
177364.0%
 
23197116.7%
 
35084126.5%
 
4154588.1%
 
5108275.6%
 
ValueCountFrequency (%) 
5108275.6%
 
4154588.1%
 
35084126.5%
 
23197116.7%
 
177364.0%
 
02353812.3%
 

KBA13_MAZDA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.95156407
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:58.310264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9786336186
Coefficient of variation (CV)0.3315644165
Kurtosis-0.170283206
Mean2.95156407
Median Absolute Deviation (MAD)1
Skewness0.1058175308
Sum414314
Variance0.9577237594
MonotocityNot monotonic
2020-11-30T23:55:58.393995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36279532.8%
 
23285117.1%
 
42566213.4%
 
596295.0%
 
194344.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
194344.9%
 
23285117.1%
 
36279532.8%
 
42566213.4%
 
596295.0%
 
ValueCountFrequency (%) 
596295.0%
 
42566213.4%
 
36279532.8%
 
23285117.1%
 
194344.9%
 

KBA13_MERCEDES
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.413917405
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:58.484086image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9332138874
Coefficient of variation (CV)0.2733557309
Kurtosis-0.2491780571
Mean3.413917405
Median Absolute Deviation (MAD)1
Skewness-0.01364322894
Sum479215
Variance0.8708881596
MonotocityNot monotonic
2020-11-30T23:55:58.567207image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36251732.6%
 
43955520.6%
 
51991510.4%
 
2154858.1%
 
128991.5%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
128991.5%
 
2154858.1%
 
36251732.6%
 
43955520.6%
 
51991510.4%
 
ValueCountFrequency (%) 
51991510.4%
 
43955520.6%
 
36251732.6%
 
2154858.1%
 
128991.5%
 

KBA13_MOTOR
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Memory size1.5 MiB
3
84318 
2
25478 
4
18343 
1
12232 
ValueCountFrequency (%) 
38431844.0%
 
22547813.3%
 
4183439.6%
 
1122326.4%
 
(Missing)5128126.8%
 
2020-11-30T23:55:58.674061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
n10256217.8%
 
38431814.7%
 
a512818.9%
 
2254784.4%
 
4183433.2%
 
1122322.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28074248.8%
 
Lowercase Letter15384326.8%
 
Other Punctuation14037124.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014037150.0%
 
38431830.0%
 
2254789.1%
 
4183436.5%
 
1122324.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.140371100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42111373.2%
 
Latin15384326.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
.14037133.3%
 
014037133.3%
 
38431820.0%
 
2254786.1%
 
4183434.4%
 
1122322.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10256266.7%
 
a5128133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.14037124.4%
 
014037124.4%
 
n10256217.8%
 
38431814.7%
 
a512818.9%
 
2254784.4%
 
4183433.2%
 
1122322.1%
 

KBA13_NISSAN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.817305569
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:58.762859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9832312116
Coefficient of variation (CV)0.3489970071
Kurtosis-0.1951323939
Mean2.817305569
Median Absolute Deviation (MAD)1
Skewness0.1318263908
Sum395468
Variance0.9667436155
MonotocityNot monotonic
2020-11-30T23:55:58.845416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36049731.6%
 
23734119.5%
 
42236211.7%
 
1127526.7%
 
574193.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1127526.7%
 
23734119.5%
 
36049731.6%
 
42236211.7%
 
574193.9%
 
ValueCountFrequency (%) 
574193.9%
 
42236211.7%
 
36049731.6%
 
23734119.5%
 
1127526.7%
 

KBA13_OPEL
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.858225702
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:58.937534image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.094689005
Coefficient of variation (CV)0.3829959979
Kurtosis-0.5142690669
Mean2.858225702
Median Absolute Deviation (MAD)1
Skewness0.08181547442
Sum401212
Variance1.198344017
MonotocityNot monotonic
2020-11-30T23:55:59.019560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35479328.6%
 
23233416.9%
 
42475912.9%
 
1173249.0%
 
5111615.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1173249.0%
 
23233416.9%
 
35479328.6%
 
42475912.9%
 
5111615.8%
 
ValueCountFrequency (%) 
5111615.8%
 
42475912.9%
 
35479328.6%
 
23233416.9%
 
1173249.0%
 

KBA13_PEUGEOT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.129841634
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:59.107935image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.010289396
Coefficient of variation (CV)0.3227924971
Kurtosis-0.2908385626
Mean3.129841634
Median Absolute Deviation (MAD)1
Skewness0.004353375207
Sum439339
Variance1.020684665
MonotocityNot monotonic
2020-11-30T23:55:59.190639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36107931.9%
 
43128116.3%
 
22589513.5%
 
5142687.4%
 
178484.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
178484.1%
 
22589513.5%
 
36107931.9%
 
43128116.3%
 
5142687.4%
 
ValueCountFrequency (%) 
5142687.4%
 
43128116.3%
 
36107931.9%
 
22589513.5%
 
178484.1%
 

KBA13_RENAULT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.8842211
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:59.281452image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.002775806
Coefficient of variation (CV)0.3476764683
Kurtosis-0.2260894159
Mean2.8842211
Median Absolute Deviation (MAD)1
Skewness0.08544963949
Sum404861
Variance1.005559317
MonotocityNot monotonic
2020-11-30T23:55:59.366528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36145232.1%
 
23341717.4%
 
42413112.6%
 
1124276.5%
 
589444.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1124276.5%
 
23341717.4%
 
36145232.1%
 
42413112.6%
 
589444.7%
 
ValueCountFrequency (%) 
589444.7%
 
42413112.6%
 
36145232.1%
 
23341717.4%
 
1124276.5%
 

KBA13_SEG_GELAENDEWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.144937345
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:59.456873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9374550868
Coefficient of variation (CV)0.2980838675
Kurtosis-0.06045106109
Mean3.144937345
Median Absolute Deviation (MAD)1
Skewness0.02463697551
Sum441458
Variance0.8788220398
MonotocityNot monotonic
2020-11-30T23:55:59.539917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36646934.7%
 
43229416.9%
 
22413912.6%
 
5117826.1%
 
156873.0%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
156873.0%
 
22413912.6%
 
36646934.7%
 
43229416.9%
 
5117826.1%
 
ValueCountFrequency (%) 
5117826.1%
 
43229416.9%
 
36646934.7%
 
22413912.6%
 
156873.0%
 

KBA13_SEG_GROSSRAUMVANS
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.30824743
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:59.629627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9627878663
Coefficient of variation (CV)0.2910265591
Kurtosis-0.2221099341
Mean3.30824743
Median Absolute Deviation (MAD)1
Skewness-0.03356944773
Sum464382
Variance0.9269604755
MonotocityNot monotonic
2020-11-30T23:55:59.711794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36237932.5%
 
43689319.2%
 
21927810.1%
 
5173249.0%
 
144972.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
144972.3%
 
21927810.1%
 
36237932.5%
 
43689319.2%
 
5173249.0%
 
ValueCountFrequency (%) 
5173249.0%
 
43689319.2%
 
36237932.5%
 
21927810.1%
 
144972.3%
 

KBA13_SEG_KLEINST
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.816992114
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:59.801645image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.010607382
Coefficient of variation (CV)0.3587540686
Kurtosis-0.286821032
Mean2.816992114
Median Absolute Deviation (MAD)1
Skewness0.05069935292
Sum395424
Variance1.021327281
MonotocityNot monotonic
2020-11-30T23:55:59.884012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36050231.6%
 
23365717.6%
 
42348012.3%
 
1152448.0%
 
574883.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1152448.0%
 
23365717.6%
 
36050231.6%
 
42348012.3%
 
574883.9%
 
ValueCountFrequency (%) 
574883.9%
 
42348012.3%
 
36050231.6%
 
23365717.6%
 
1152448.0%
 

KBA13_SEG_KLEINWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.760848038
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:55:59.975785image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9701304845
Coefficient of variation (CV)0.3513885846
Kurtosis-0.2036006464
Mean2.760848038
Median Absolute Deviation (MAD)1
Skewness0.01583038427
Sum387543
Variance0.941153157
MonotocityNot monotonic
2020-11-30T23:56:00.062349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36308332.9%
 
23477018.1%
 
42156811.3%
 
1155678.1%
 
553832.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1155678.1%
 
23477018.1%
 
36308332.9%
 
42156811.3%
 
553832.8%
 
ValueCountFrequency (%) 
553832.8%
 
42156811.3%
 
36308332.9%
 
23477018.1%
 
1155678.1%
 

KBA13_SEG_KOMPAKTKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.743964209
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:00.152214image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9203209345
Coefficient of variation (CV)0.3353983013
Kurtosis-0.005413931325
Mean2.743964209
Median Absolute Deviation (MAD)1
Skewness0.02440108363
Sum385173
Variance0.8469906225
MonotocityNot monotonic
2020-11-30T23:56:00.236478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36679934.9%
 
23649119.0%
 
4189079.9%
 
1136767.1%
 
544982.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1136767.1%
 
23649119.0%
 
36679934.9%
 
4189079.9%
 
544982.3%
 
ValueCountFrequency (%) 
544982.3%
 
4189079.9%
 
36679934.9%
 
23649119.0%
 
1136767.1%
 

KBA13_SEG_MINIVANS
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.081491191
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:00.330901image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9767943022
Coefficient of variation (CV)0.3169875367
Kurtosis-0.1755041276
Mean3.081491191
Median Absolute Deviation (MAD)1
Skewness0.03718431282
Sum432552
Variance0.9541271088
MonotocityNot monotonic
2020-11-30T23:56:00.418814image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36375633.3%
 
42994515.6%
 
22725414.2%
 
5118956.2%
 
175213.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
175213.9%
 
22725414.2%
 
36375633.3%
 
42994515.6%
 
5118956.2%
 
ValueCountFrequency (%) 
5118956.2%
 
42994515.6%
 
36375633.3%
 
22725414.2%
 
175213.9%
 

KBA13_SEG_MINIWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.114311361
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:00.509366image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9477620495
Coefficient of variation (CV)0.3043247575
Kurtosis-0.09167807371
Mean3.114311361
Median Absolute Deviation (MAD)1
Skewness0.02559454704
Sum437159
Variance0.8982529024
MonotocityNot monotonic
2020-11-30T23:56:00.592577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36564234.3%
 
43144516.4%
 
22555313.3%
 
5114046.0%
 
163273.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
163273.3%
 
22555313.3%
 
36564234.3%
 
43144516.4%
 
5114046.0%
 
ValueCountFrequency (%) 
5114046.0%
 
43144516.4%
 
36564234.3%
 
22555313.3%
 
163273.3%
 

KBA13_SEG_MITTELKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.981142829
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:00.684862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9739906193
Coefficient of variation (CV)0.3267171938
Kurtosis-0.1588749295
Mean2.981142829
Median Absolute Deviation (MAD)1
Skewness0.05401156701
Sum418466
Variance0.9486577265
MonotocityNot monotonic
2020-11-30T23:56:00.767315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36351933.1%
 
23070916.0%
 
42735614.3%
 
595705.0%
 
192174.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
192174.8%
 
23070916.0%
 
36351933.1%
 
42735614.3%
 
595705.0%
 
ValueCountFrequency (%) 
595705.0%
 
42735614.3%
 
36351933.1%
 
23070916.0%
 
192174.8%
 

KBA13_SEG_OBEREMITTELKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.355237193
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:00.857701image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9353661649
Coefficient of variation (CV)0.2787779555
Kurtosis-0.2301126313
Mean3.355237193
Median Absolute Deviation (MAD)1
Skewness0.02969534055
Sum470978
Variance0.8749098623
MonotocityNot monotonic
2020-11-30T23:56:00.940353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36413633.5%
 
43721519.4%
 
5182759.5%
 
2175909.2%
 
131551.6%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
131551.6%
 
2175909.2%
 
36413633.5%
 
43721519.4%
 
5182759.5%
 
ValueCountFrequency (%) 
5182759.5%
 
43721519.4%
 
36413633.5%
 
2175909.2%
 
131551.6%
 

KBA13_SEG_OBERKLASSE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.728291456
Minimum0
Maximum5
Zeros14998
Zeros (%)7.8%
Memory size1.5 MiB
2020-11-30T23:56:01.026661image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.474938551
Coefficient of variation (CV)0.5406088662
Kurtosis-0.6630675495
Mean2.728291456
Median Absolute Deviation (MAD)1
Skewness-0.3084380804
Sum382973
Variance2.175443728
MonotocityNot monotonic
2020-11-30T23:56:01.108742image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35558629.0%
 
51911410.0%
 
4185869.7%
 
1178739.3%
 
0149987.8%
 
2142147.4%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
0149987.8%
 
1178739.3%
 
2142147.4%
 
35558629.0%
 
4185869.7%
 
51911410.0%
 
ValueCountFrequency (%) 
51911410.0%
 
4185869.7%
 
35558629.0%
 
2142147.4%
 
1178739.3%
 
0149987.8%
 

KBA13_SEG_SONSTIGE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.96209331
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:01.189134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9052548519
Coefficient of variation (CV)0.3056132124
Kurtosis0.008300140446
Mean2.96209331
Median Absolute Deviation (MAD)1
Skewness0.1689217102
Sum415792
Variance0.8194863468
MonotocityNot monotonic
2020-11-30T23:56:01.279699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36680534.9%
 
23413617.8%
 
42554113.3%
 
577634.1%
 
161263.2%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
161263.2%
 
23413617.8%
 
36680534.9%
 
42554113.3%
 
577634.1%
 
ValueCountFrequency (%) 
577634.1%
 
42554113.3%
 
36680534.9%
 
23413617.8%
 
161263.2%
 

KBA13_SEG_SPORTWAGEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.956465367
Minimum0
Maximum5
Zeros14430
Zeros (%)7.5%
Memory size1.5 MiB
2020-11-30T23:56:01.368333image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.445583832
Coefficient of variation (CV)0.4889567956
Kurtosis-0.2886516217
Mean2.956465367
Median Absolute Deviation (MAD)1
Skewness-0.5032481522
Sum415002
Variance2.089712616
MonotocityNot monotonic
2020-11-30T23:56:01.451186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35469028.5%
 
52380612.4%
 
42201611.5%
 
2184099.6%
 
0144307.5%
 
170203.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
0144307.5%
 
170203.7%
 
2184099.6%
 
35469028.5%
 
42201611.5%
 
52380612.4%
 
ValueCountFrequency (%) 
52380612.4%
 
42201611.5%
 
35469028.5%
 
2184099.6%
 
170203.7%
 
0144307.5%
 

KBA13_SEG_UTILITIES
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.0800379
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:01.533067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9400335058
Coefficient of variation (CV)0.3052019282
Kurtosis-0.08997424617
Mean3.0800379
Median Absolute Deviation (MAD)1
Skewness0.05138409028
Sum432348
Variance0.8836629921
MonotocityNot monotonic
2020-11-30T23:56:01.616425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36561034.2%
 
43053315.9%
 
22750214.3%
 
5104145.4%
 
163123.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
163123.3%
 
22750214.3%
 
36561034.2%
 
43053315.9%
 
5104145.4%
 
ValueCountFrequency (%) 
5104145.4%
 
43053315.9%
 
36561034.2%
 
22750214.3%
 
163123.3%
 

KBA13_SEG_VAN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.2142964
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:01.707120image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9716826647
Coefficient of variation (CV)0.3023002685
Kurtosis-0.1993891519
Mean3.2142964
Median Absolute Deviation (MAD)1
Skewness-0.01399526871
Sum451194
Variance0.9441672009
MonotocityNot monotonic
2020-11-30T23:56:01.789510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36307532.9%
 
43429117.9%
 
22244411.7%
 
5148397.7%
 
157223.0%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
157223.0%
 
22244411.7%
 
36307532.9%
 
43429117.9%
 
5148397.7%
 
ValueCountFrequency (%) 
5148397.7%
 
43429117.9%
 
36307532.9%
 
22244411.7%
 
157223.0%
 

KBA13_SEG_WOHNMOBILE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.669404649
Minimum0
Maximum5
Zeros15839
Zeros (%)8.3%
Memory size1.5 MiB
2020-11-30T23:56:01.876892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.404803512
Coefficient of variation (CV)0.5262609821
Kurtosis-0.4239869863
Mean2.669404649
Median Absolute Deviation (MAD)1
Skewness-0.3093967445
Sum374707
Variance1.973472908
MonotocityNot monotonic
2020-11-30T23:56:01.958635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
35423128.3%
 
22573213.4%
 
4180679.4%
 
0158398.3%
 
5154458.1%
 
1110575.8%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
0158398.3%
 
1110575.8%
 
22573213.4%
 
35423128.3%
 
4180679.4%
 
5154458.1%
 
ValueCountFrequency (%) 
5154458.1%
 
4180679.4%
 
35423128.3%
 
22573213.4%
 
1110575.8%
 
0158398.3%
 

KBA13_SITZE_4
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.454531207
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:02.040024image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9398393676
Coefficient of variation (CV)0.2720598864
Kurtosis-0.2819040442
Mean3.454531207
Median Absolute Deviation (MAD)1
Skewness-0.04126574968
Sum484916
Variance0.8832980368
MonotocityNot monotonic
2020-11-30T23:56:02.125664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36129032.0%
 
44018421.0%
 
52178811.4%
 
2142617.4%
 
128481.5%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
128481.5%
 
2142617.4%
 
36129032.0%
 
44018421.0%
 
52178811.4%
 
ValueCountFrequency (%) 
52178811.4%
 
44018421.0%
 
36129032.0%
 
2142617.4%
 
128481.5%
 

KBA13_SITZE_5
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.514158907
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:02.215456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9517257628
Coefficient of variation (CV)0.3785463838
Kurtosis-0.2989844162
Mean2.514158907
Median Absolute Deviation (MAD)1
Skewness0.08447406193
Sum352915
Variance0.9057819276
MonotocityNot monotonic
2020-11-30T23:56:02.297876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35979431.2%
 
24060521.2%
 
12353312.3%
 
4134057.0%
 
530341.6%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
12353312.3%
 
24060521.2%
 
35979431.2%
 
4134057.0%
 
530341.6%
 
ValueCountFrequency (%) 
530341.6%
 
4134057.0%
 
35979431.2%
 
24060521.2%
 
12353312.3%
 

KBA13_SITZE_6
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.33105841
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:04.362534image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9778860875
Coefficient of variation (CV)0.2935661784
Kurtosis-0.2894903016
Mean3.33105841
Median Absolute Deviation (MAD)1
Skewness-0.02403242039
Sum467584
Variance0.9562612001
MonotocityNot monotonic
2020-11-30T23:56:04.446888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36177532.2%
 
43590018.7%
 
51923510.0%
 
2190239.9%
 
144382.3%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
144382.3%
 
2190239.9%
 
36177532.2%
 
43590018.7%
 
51923510.0%
 
ValueCountFrequency (%) 
51923510.0%
 
43590018.7%
 
36177532.2%
 
2190239.9%
 
144382.3%
 

KBA13_TOYOTA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.057426391
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:04.537629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9834713156
Coefficient of variation (CV)0.3216663918
Kurtosis-0.1829946298
Mean3.057426391
Median Absolute Deviation (MAD)1
Skewness0.07139193922
Sum429174
Variance0.9672158286
MonotocityNot monotonic
2020-11-30T23:56:04.619962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36378033.3%
 
22847314.9%
 
42823814.7%
 
5120146.3%
 
178664.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
178664.1%
 
22847314.9%
 
36378033.3%
 
42823814.7%
 
5120146.3%
 
ValueCountFrequency (%) 
5120146.3%
 
42823814.7%
 
36378033.3%
 
22847314.9%
 
178664.1%
 

KBA13_VORB_0
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.37562602
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:04.712777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9566412849
Coefficient of variation (CV)0.2833967031
Kurtosis-0.3455956916
Mean3.37562602
Median Absolute Deviation (MAD)1
Skewness-0.002431504675
Sum473840
Variance0.915162548
MonotocityNot monotonic
2020-11-30T23:56:04.795695image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36082531.7%
 
43815419.9%
 
51971810.3%
 
2184859.6%
 
131891.7%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
131891.7%
 
2184859.6%
 
36082531.7%
 
43815419.9%
 
51971810.3%
 
ValueCountFrequency (%) 
51971810.3%
 
43815419.9%
 
36082531.7%
 
2184859.6%
 
131891.7%
 

KBA13_VORB_1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.047132242
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:04.886678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9253622604
Coefficient of variation (CV)0.3036829999
Kurtosis-0.0280992086
Mean3.047132242
Median Absolute Deviation (MAD)1
Skewness0.005265661408
Sum427729
Variance0.856295313
MonotocityNot monotonic
2020-11-30T23:56:04.969806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36663134.8%
 
43055315.9%
 
22759714.4%
 
587104.5%
 
168803.6%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
168803.6%
 
22759714.4%
 
36663134.8%
 
43055315.9%
 
587104.5%
 
ValueCountFrequency (%) 
587104.5%
 
43055315.9%
 
36663134.8%
 
22759714.4%
 
168803.6%
 

KBA13_VORB_1_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.852861346
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:05.060223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9614311831
Coefficient of variation (CV)0.3370059272
Kurtosis-0.1637057856
Mean2.852861346
Median Absolute Deviation (MAD)1
Skewness-0.03117309276
Sum400459
Variance0.9243499198
MonotocityNot monotonic
2020-11-30T23:56:05.142650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36422733.5%
 
23213216.8%
 
42513013.1%
 
1128546.7%
 
560283.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
1128546.7%
 
23213216.8%
 
36422733.5%
 
42513013.1%
 
560283.1%
 
ValueCountFrequency (%) 
560283.1%
 
42513013.1%
 
36422733.5%
 
23213216.8%
 
1128546.7%
 

KBA13_VORB_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.854307514
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:05.232745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.921045844
Coefficient of variation (CV)0.3226862696
Kurtosis-0.01913213754
Mean2.854307514
Median Absolute Deviation (MAD)1
Skewness0.08043723629
Sum400662
Variance0.8483254468
MonotocityNot monotonic
2020-11-30T23:56:05.316028image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36559834.2%
 
23586318.7%
 
42314812.1%
 
198155.1%
 
559473.1%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
198155.1%
 
23586318.7%
 
36559834.2%
 
42314812.1%
 
559473.1%
 
ValueCountFrequency (%) 
559473.1%
 
42314812.1%
 
36559834.2%
 
23586318.7%
 
198155.1%
 

KBA13_VORB_3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean2.011911292
Minimum0
Maximum5
Zeros31766
Zeros (%)16.6%
Memory size1.5 MiB
2020-11-30T23:56:05.404016image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.375629499
Coefficient of variation (CV)0.6837426202
Kurtosis-0.759494375
Mean2.011911292
Median Absolute Deviation (MAD)1
Skewness-0.0546854007
Sum282414
Variance1.892356517
MonotocityNot monotonic
2020-11-30T23:56:05.483811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34312222.5%
 
23894020.3%
 
03176616.6%
 
1120266.3%
 
494434.9%
 
550742.6%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
03176616.6%
 
1120266.3%
 
23894020.3%
 
34312222.5%
 
494434.9%
 
550742.6%
 
ValueCountFrequency (%) 
550742.6%
 
494434.9%
 
34312222.5%
 
23894020.3%
 
1120266.3%
 
03176616.6%
 

KBA13_VW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing51281
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean3.002358037
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:05.563412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9728604006
Coefficient of variation (CV)0.324032107
Kurtosis-0.1273016851
Mean3.002358037
Median Absolute Deviation (MAD)1
Skewness0.00197430622
Sum421444
Variance0.946457359
MonotocityNot monotonic
2020-11-30T23:56:05.646431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36460633.7%
 
42838914.8%
 
22834614.8%
 
595875.0%
 
194434.9%
 
(Missing)5128126.8%
 
ValueCountFrequency (%) 
194434.9%
 
22834614.8%
 
36460633.7%
 
42838914.8%
 
595875.0%
 
ValueCountFrequency (%) 
595875.0%
 
42838914.8%
 
36460633.7%
 
22834614.8%
 
194434.9%
 

KK_KUNDENTYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing111937
Missing (%)58.4%
Infinite0
Infinite (%)0.0%
Mean3.421802672
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:05.735090image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.623889984
Coefficient of variation (CV)0.4745714874
Kurtosis-1.149253485
Mean3.421802672
Median Absolute Deviation (MAD)1
Skewness0.1285611156
Sum272769
Variance2.637018679
MonotocityNot monotonic
2020-11-30T23:56:05.820354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
3175119.1%
 
2153948.0%
 
5127416.6%
 
4116536.1%
 
6113435.9%
 
1110735.8%
 
(Missing)11193758.4%
 
ValueCountFrequency (%) 
1110735.8%
 
2153948.0%
 
3175119.1%
 
4116536.1%
 
5127416.6%
 
6113435.9%
 
ValueCountFrequency (%) 
6113435.9%
 
5127416.6%
 
4116536.1%
 
3175119.1%
 
2153948.0%
 
1110735.8%
 

KKK
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing54260
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean2.321568941
Minimum0
Maximum4
Zeros5804
Zeros (%)3.0%
Memory size1.5 MiB
2020-11-30T23:56:05.904539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.100511535
Coefficient of variation (CV)0.4740378437
Kurtosis-0.8173424217
Mean2.321568941
Median Absolute Deviation (MAD)1
Skewness-0.1312618203
Sum318965
Variance1.211125638
MonotocityNot monotonic
2020-11-30T23:56:05.988705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
34073921.3%
 
24004920.9%
 
12885015.1%
 
42195011.5%
 
058043.0%
 
(Missing)5426028.3%
 
ValueCountFrequency (%) 
058043.0%
 
12885015.1%
 
24004920.9%
 
34073921.3%
 
42195011.5%
 
ValueCountFrequency (%) 
42195011.5%
 
34073921.3%
 
24004920.9%
 
12885015.1%
 
058043.0%
 

KOMBIALTER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.997839835
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:06.082279image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median4
Q34
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.340319837
Coefficient of variation (CV)0.4682662739
Kurtosis-0.6574909575
Mean4.997839835
Median Absolute Deviation (MAD)0
Skewness0.9911719967
Sum957846
Variance5.47709694
MonotocityNot monotonic
2020-11-30T23:56:06.166168image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
410917957.0%
 
94705124.6%
 
32834414.8%
 
255612.9%
 
115170.8%
 
ValueCountFrequency (%) 
115170.8%
 
255612.9%
 
32834414.8%
 
410917957.0%
 
94705124.6%
 
ValueCountFrequency (%) 
94705124.6%
 
410917957.0%
 
32834414.8%
 
255612.9%
 
115170.8%
 

KONSUMNAEHE
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing46651
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean3.129978414
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:06.253334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.439739672
Coefficient of variation (CV)0.4599838981
Kurtosis-1.056228765
Mean3.129978414
Median Absolute Deviation (MAD)1
Skewness0.02010129011
Sum453850
Variance2.072850323
MonotocityNot monotonic
2020-11-30T23:56:06.332434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
33438317.9%
 
52840514.8%
 
42799514.6%
 
12588613.5%
 
22485713.0%
 
632291.7%
 
72460.1%
 
(Missing)4665124.3%
 
ValueCountFrequency (%) 
12588613.5%
 
22485713.0%
 
33438317.9%
 
42799514.6%
 
52840514.8%
 
632291.7%
 
72460.1%
 
ValueCountFrequency (%) 
72460.1%
 
632291.7%
 
52840514.8%
 
42799514.6%
 
33438317.9%
 
22485713.0%
 
12588613.5%
 

KONSUMZELLE
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Memory size1.5 MiB
0
116619 
1
25106 
(Missing)
49927 
ValueCountFrequency (%) 
011661960.8%
 
12510613.1%
 
(Missing)4992726.1%
 

LP_FAMILIE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct12
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean4.254448389
Minimum0
Maximum11
Zeros47369
Zeros (%)24.7%
Memory size1.5 MiB
2020-11-30T23:56:06.424164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)10

Descriptive statistics

Standard deviation4.492806628
Coefficient of variation (CV)1.056025651
Kurtosis-1.578131385
Mean4.254448389
Median Absolute Deviation (MAD)2
Skewness0.5245495186
Sum801704
Variance20.18531139
MonotocityNot monotonic
2020-11-30T23:56:06.503668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
04736924.7%
 
14076921.3%
 
103656819.1%
 
22893715.1%
 
112228911.6%
 
846862.4%
 
729601.5%
 
924281.3%
 
59030.5%
 
68310.4%
 
45440.3%
 
31550.1%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
04736924.7%
 
14076921.3%
 
22893715.1%
 
31550.1%
 
45440.3%
 
59030.5%
 
68310.4%
 
729601.5%
 
846862.4%
 
924281.3%
 
ValueCountFrequency (%) 
112228911.6%
 
103656819.1%
 
924281.3%
 
846862.4%
 
729601.5%
 
68310.4%
 
59030.5%
 
45440.3%
 
31550.1%
 
22893715.1%
 

LP_FAMILIE_GROB
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean2.355043277
Minimum0
Maximum5
Zeros47369
Zeros (%)24.7%
Memory size1.5 MiB
2020-11-30T23:56:06.593025image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.052141644
Coefficient of variation (CV)0.8713817129
Kurtosis-1.606584382
Mean2.355043277
Median Absolute Deviation (MAD)2
Skewness0.2767634688
Sum443782
Variance4.211285328
MonotocityNot monotonic
2020-11-30T23:56:06.680560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
56128532.0%
 
04736924.7%
 
14076921.3%
 
22893715.1%
 
484774.4%
 
316020.8%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
04736924.7%
 
14076921.3%
 
22893715.1%
 
316020.8%
 
484774.4%
 
56128532.0%
 
ValueCountFrequency (%) 
56128532.0%
 
484774.4%
 
316020.8%
 
22893715.1%
 
14076921.3%
 
04736924.7%
 

LP_LEBENSPHASE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean18.18157069
Minimum0
Maximum40
Zeros47840
Zeros (%)25.0%
Memory size1.5 MiB
2020-11-30T23:56:06.782344image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16
Q336
95-th percentile40
Maximum40
Range40
Interquartile range (IQR)36

Descriptive statistics

Standard deviation15.00998521
Coefficient of variation (CV)0.8255604238
Kurtosis-1.479585124
Mean18.18157069
Median Absolute Deviation (MAD)16
Skewness0.1823497672
Sum3426117
Variance225.2996559
MonotocityNot monotonic
2020-11-30T23:56:06.894860image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%) 
04784025.0%
 
40182999.5%
 
20108515.7%
 
1399725.2%
 
3688214.6%
 
3886484.5%
 
3967853.5%
 
666463.5%
 
862973.3%
 
1961433.2%
 
1259513.1%
 
3254152.8%
 
3745922.4%
 
3139832.1%
 
1639622.1%
 
2837091.9%
 
1734751.8%
 
1532521.7%
 
929391.5%
 
2725561.3%
 
522611.2%
 
1119851.0%
 
3517840.9%
 
717000.9%
 
2311130.6%
 
Other values (16)94604.9%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
04784025.0%
 
15530.3%
 
26630.3%
 
32580.1%
 
44340.2%
 
522611.2%
 
666463.5%
 
717000.9%
 
862973.3%
 
929391.5%
 
ValueCountFrequency (%) 
40182999.5%
 
3967853.5%
 
3886484.5%
 
3745922.4%
 
3688214.6%
 
3517840.9%
 
349190.5%
 
336230.3%
 
3254152.8%
 
3139832.1%
 

LP_LEBENSPHASE_GROB
Real number (ℝ≥0)

MISSING
ZEROS

Distinct13
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean5.422693816
Minimum0
Maximum12
Zeros47728
Zeros (%)24.9%
Memory size1.5 MiB
2020-11-30T23:56:06.996164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q312
95-th percentile12
Maximum12
Range12
Interquartile range (IQR)12

Descriptive statistics

Standard deviation4.717907433
Coefficient of variation (CV)0.8700302088
Kurtosis-1.487400067
Mean5.422693816
Median Absolute Deviation (MAD)4
Skewness0.3181147429
Sum1021847
Variance22.25865055
MonotocityNot monotonic
2020-11-30T23:56:07.088023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
04772824.9%
 
124714524.6%
 
32173911.3%
 
52106911.0%
 
2169048.8%
 
1093984.9%
 
478514.1%
 
872803.8%
 
1133261.7%
 
119081.0%
 
616020.8%
 
912920.7%
 
711970.6%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
04772824.9%
 
119081.0%
 
2169048.8%
 
32173911.3%
 
478514.1%
 
52106911.0%
 
616020.8%
 
711970.6%
 
872803.8%
 
912920.7%
 
ValueCountFrequency (%) 
124714524.6%
 
1133261.7%
 
1093984.9%
 
912920.7%
 
872803.8%
 
711970.6%
 
616020.8%
 
52106911.0%
 
478514.1%
 
32173911.3%
 

LP_STATUS_FEIN
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean6.687909615
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:07.177972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median7
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.090572785
Coefficient of variation (CV)0.46211342
Kurtosis-1.14949574
Mean6.687909615
Median Absolute Deviation (MAD)3
Skewness-0.4256118986
Sum1260263
Variance9.551640139
MonotocityNot monotonic
2020-11-30T23:56:07.255648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
105465328.5%
 
54191221.9%
 
93291617.2%
 
11927110.1%
 
3153648.0%
 
7105745.5%
 
665023.4%
 
450042.6%
 
214040.7%
 
88390.4%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
11927110.1%
 
214040.7%
 
3153648.0%
 
450042.6%
 
54191221.9%
 
665023.4%
 
7105745.5%
 
88390.4%
 
93291617.2%
 
105465328.5%
 
ValueCountFrequency (%) 
105465328.5%
 
93291617.2%
 
88390.4%
 
7105745.5%
 
665023.4%
 
54191221.9%
 
450042.6%
 
3153648.0%
 
214040.7%
 
11927110.1%
 

LP_STATUS_GROB
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean3.209250739
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:07.337514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.436958279
Coefficient of variation (CV)0.4477550669
Kurtosis-1.505216079
Mean3.209250739
Median Absolute Deviation (MAD)1
Skewness-0.004799456829
Sum604748
Variance2.064849097
MonotocityNot monotonic
2020-11-30T23:56:07.420641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
26228032.5%
 
55465328.5%
 
43375517.6%
 
12067510.8%
 
3170768.9%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
12067510.8%
 
26228032.5%
 
3170768.9%
 
43375517.6%
 
55465328.5%
 
ValueCountFrequency (%) 
55465328.5%
 
43375517.6%
 
3170768.9%
 
26228032.5%
 
12067510.8%
 

MIN_GEBAEUDEJAHR
Real number (ℝ≥0)

MISSING

Distinct32
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean1993.056659
Minimum1985
Maximum2016
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:07.522081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile1992
Q11992
median1992
Q31992
95-th percentile1999
Maximum2016
Range31
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.080241078
Coefficient of variation (CV)0.001545485957
Kurtosis16.6545333
Mean1993.056659
Median Absolute Deviation (MAD)0
Skewness3.801723463
Sum282465955
Variance9.487885101
MonotocityNot monotonic
2020-11-30T23:56:07.621965image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%) 
199210643855.5%
 
1994117146.1%
 
199340842.1%
 
199528961.5%
 
199626181.4%
 
199725241.3%
 
200012410.6%
 
199111210.6%
 
199010220.5%
 
20019730.5%
 
20057410.4%
 
20027000.4%
 
19996490.3%
 
19986090.3%
 
19895810.3%
 
20035240.3%
 
20044550.2%
 
20073650.2%
 
20083520.2%
 
20092970.2%
 
20062970.2%
 
20112480.1%
 
19882450.1%
 
20122190.1%
 
20102130.1%
 
Other values (7)5990.3%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
198516< 0.1%
 
198638< 0.1%
 
19871180.1%
 
19882450.1%
 
19895810.3%
 
199010220.5%
 
199111210.6%
 
199210643855.5%
 
199340842.1%
 
1994117146.1%
 
ValueCountFrequency (%) 
20164< 0.1%
 
201588< 0.1%
 
20141470.1%
 
20131880.1%
 
20122190.1%
 
20112480.1%
 
20102130.1%
 
20092970.2%
 
20083520.2%
 
20073650.2%
 

MOBI_RASTER
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean2.90036338
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:07.714021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.527411359
Coefficient of variation (CV)0.5266275839
Kurtosis-1.119048648
Mean2.90036338
Median Absolute Deviation (MAD)1
Skewness0.2284179168
Sum411054
Variance2.33298546
MonotocityNot monotonic
2020-11-30T23:56:07.800126image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
13768819.7%
 
32987815.6%
 
42472912.9%
 
22254311.8%
 
52159211.3%
 
652952.8%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
13768819.7%
 
22254311.8%
 
32987815.6%
 
42472912.9%
 
52159211.3%
 
652952.8%
 
ValueCountFrequency (%) 
652952.8%
 
52159211.3%
 
42472912.9%
 
32987815.6%
 
22254311.8%
 
13768819.7%
 

MOBI_REGIO
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing55980
Missing (%)29.2%
Infinite0
Infinite (%)0.0%
Mean3.627424966
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:07.880856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.28244416
Coefficient of variation (CV)0.3535411958
Kurtosis-0.5995691426
Mean3.627424966
Median Absolute Deviation (MAD)1
Skewness-0.662550733
Sum492140
Variance1.644663024
MonotocityNot monotonic
2020-11-30T23:56:07.967582image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
54265122.3%
 
43914820.4%
 
32739914.3%
 
1132046.9%
 
2131826.9%
 
688< 0.1%
 
(Missing)5598029.2%
 
ValueCountFrequency (%) 
1132046.9%
 
2131826.9%
 
32739914.3%
 
43914820.4%
 
54265122.3%
 
688< 0.1%
 
ValueCountFrequency (%) 
688< 0.1%
 
54265122.3%
 
43914820.4%
 
32739914.3%
 
2131826.9%
 
1132046.9%
 

NATIONALITAET_KZ
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
1
139027 
0
48750 
2
 
2422
3
 
1453
ValueCountFrequency (%) 
113902772.5%
 
04875025.4%
 
224221.3%
 
314530.8%
 
2020-11-30T23:56:08.073769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
113902772.5%
 
04875025.4%
 
224221.3%
 
314530.8%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number191652100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
113902772.5%
 
04875025.4%
 
224221.3%
 
314530.8%
 

Most occurring scripts

ValueCountFrequency (%) 
Common191652100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
113902772.5%
 
04875025.4%
 
224221.3%
 
314530.8%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII191652100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
113902772.5%
 
04875025.4%
 
224221.3%
 
314530.8%
 

ONLINE_AFFINITAET
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean2.764326917
Minimum0
Maximum5
Zeros4110
Zeros (%)2.1%
Memory size1.5 MiB
2020-11-30T23:56:08.159705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.266049511
Coefficient of variation (CV)0.4579955803
Kurtosis-0.7882827556
Mean2.764326917
Median Absolute Deviation (MAD)1
Skewness0.2320495767
Sum520907
Variance1.602881364
MonotocityNot monotonic
2020-11-30T23:56:08.245634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
27644039.9%
 
43910420.4%
 
32879115.0%
 
52131111.1%
 
1186839.7%
 
041102.1%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
041102.1%
 
1186839.7%
 
27644039.9%
 
32879115.0%
 
43910420.4%
 
52131111.1%
 
ValueCountFrequency (%) 
52131111.1%
 
43910420.4%
 
32879115.0%
 
27644039.9%
 
1186839.7%
 
041102.1%
 

ORTSGR_KLS9
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing50476
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean5.119517482
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:08.330442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q37
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.159183781
Coefficient of variation (CV)0.4217553292
Kurtosis-0.8126478698
Mean5.119517482
Median Absolute Deviation (MAD)2
Skewness0.08996363608
Sum722753
Variance4.662074599
MonotocityNot monotonic
2020-11-30T23:56:08.414988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
52874115.0%
 
42313312.1%
 
71936310.1%
 
3160468.4%
 
6134567.0%
 
2124686.5%
 
9114306.0%
 
8111085.8%
 
154312.8%
 
(Missing)5047626.3%
 
ValueCountFrequency (%) 
154312.8%
 
2124686.5%
 
3160468.4%
 
42313312.1%
 
52874115.0%
 
6134567.0%
 
71936310.1%
 
8111085.8%
 
9114306.0%
 
ValueCountFrequency (%) 
9114306.0%
 
8111085.8%
 
71936310.1%
 
6134567.0%
 
52874115.0%
 
42313312.1%
 
3160468.4%
 
2124686.5%
 
154312.8%
 

OST_WEST_KZ
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Memory size1.5 MiB
W
130382 
O
 
11343
ValueCountFrequency (%) 
W13038268.0%
 
O113435.9%
 
(Missing)4992726.1%
 
2020-11-30T23:56:08.513967image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
W13038244.7%
 
n9985434.3%
 
a4992717.1%
 
O113433.9%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter14978151.4%
 
Uppercase Letter14172548.6%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
W13038292.0%
 
O113438.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n9985466.7%
 
a4992733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin291506100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
W13038244.7%
 
n9985434.3%
 
a4992717.1%
 
O113433.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII291506100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
W13038244.7%
 
n9985434.3%
 
a4992717.1%
 
O113433.9%
 

PLZ8_ANTG1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing52764
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean2.537404239
Minimum0
Maximum4
Zeros340
Zeros (%)0.2%
Memory size1.5 MiB
2020-11-30T23:56:08.594631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9049274384
Coefficient of variation (CV)0.3566351094
Kurtosis-0.6963995068
Mean2.537404239
Median Absolute Deviation (MAD)1
Skewness-0.04181806744
Sum352415
Variance0.8188936688
MonotocityNot monotonic
2020-11-30T23:56:08.675292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
25007126.1%
 
34989426.0%
 
42133611.1%
 
1172479.0%
 
03400.2%
 
(Missing)5276427.5%
 
ValueCountFrequency (%) 
03400.2%
 
1172479.0%
 
25007126.1%
 
34989426.0%
 
42133611.1%
 
ValueCountFrequency (%) 
42133611.1%
 
34989426.0%
 
25007126.1%
 
1172479.0%
 
03400.2%
 

PLZ8_ANTG2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing52764
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean2.731510282
Minimum0
Maximum4
Zeros648
Zeros (%)0.3%
Memory size1.5 MiB
2020-11-30T23:56:08.764103image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8409224398
Coefficient of variation (CV)0.3078598845
Kurtosis-0.2526594664
Mean2.731510282
Median Absolute Deviation (MAD)1
Skewness-0.277391333
Sum379374
Variance0.7071505498
MonotocityNot monotonic
2020-11-30T23:56:08.845755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
36177832.2%
 
24293822.4%
 
42488013.0%
 
186444.5%
 
06480.3%
 
(Missing)5276427.5%
 
ValueCountFrequency (%) 
06480.3%
 
186444.5%
 
24293822.4%
 
36177832.2%
 
42488013.0%
 
ValueCountFrequency (%) 
42488013.0%
 
36177832.2%
 
24293822.4%
 
186444.5%
 
06480.3%
 

PLZ8_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing52764
Missing (%)27.5%
Memory size1.5 MiB
1
53775 
2
47221 
0
23001 
3
14891 
ValueCountFrequency (%) 
15377528.1%
 
24722124.6%
 
02300112.0%
 
3148917.8%
 
(Missing)5276427.5%
 
2020-11-30T23:56:08.955575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
016188928.2%
 
.13888824.2%
 
n10552818.4%
 
1537759.4%
 
a527649.2%
 
2472218.2%
 
3148912.6%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27777648.3%
 
Lowercase Letter15829227.5%
 
Other Punctuation13888824.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
016188958.3%
 
15377519.4%
 
24722117.0%
 
3148915.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.138888100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10552866.7%
 
a5276433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common41666472.5%
 
Latin15829227.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
016188938.9%
 
.13888833.3%
 
15377512.9%
 
24722111.3%
 
3148913.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10552866.7%
 
a5276433.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
016188928.2%
 
.13888824.2%
 
n10552818.4%
 
1537759.4%
 
a527649.2%
 
2472218.2%
 
3148912.6%
 

PLZ8_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing52764
Missing (%)27.5%
Memory size1.5 MiB
0
74829 
1
53127 
2
10932 
ValueCountFrequency (%) 
07482939.0%
 
15312727.7%
 
2109325.7%
 
(Missing)5276427.5%
 
2020-11-30T23:56:09.060025image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
021371737.2%
 
.13888824.2%
 
n10552818.4%
 
1531279.2%
 
a527649.2%
 
2109321.9%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number27777648.3%
 
Lowercase Letter15829227.5%
 
Other Punctuation13888824.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
021371776.9%
 
15312719.1%
 
2109323.9%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.138888100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10552866.7%
 
a5276433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common41666472.5%
 
Latin15829227.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
021371751.3%
 
.13888833.3%
 
15312712.8%
 
2109322.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10552866.7%
 
a5276433.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
021371737.2%
 
.13888824.2%
 
n10552818.4%
 
1531279.2%
 
a527649.2%
 
2109321.9%
 

PLZ8_BAUMAX
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing52764
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean1.556606762
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:09.144205image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.185736065
Coefficient of variation (CV)0.7617441308
Kurtosis2.957120521
Mean1.556606762
Median Absolute Deviation (MAD)0
Skewness2.088812665
Sum216194
Variance1.405970016
MonotocityNot monotonic
2020-11-30T23:56:09.226060image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
110668855.7%
 
2123156.4%
 
5101705.3%
 
448812.5%
 
348342.5%
 
(Missing)5276427.5%
 
ValueCountFrequency (%) 
110668855.7%
 
2123156.4%
 
348342.5%
 
448812.5%
 
5101705.3%
 
ValueCountFrequency (%) 
5101705.3%
 
448812.5%
 
348342.5%
 
2123156.4%
 
110668855.7%
 

PLZ8_GBZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing52764
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean3.622191982
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:09.315384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.008472036
Coefficient of variation (CV)0.2784148495
Kurtosis-0.4652710304
Mean3.622191982
Median Absolute Deviation (MAD)1
Skewness-0.2380892227
Sum503079
Variance1.017015847
MonotocityNot monotonic
2020-11-30T23:56:09.399001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35227027.3%
 
43898720.3%
 
53279817.1%
 
2114986.0%
 
133351.7%
 
(Missing)5276427.5%
 
ValueCountFrequency (%) 
133351.7%
 
2114986.0%
 
35227027.3%
 
43898720.3%
 
53279817.1%
 
ValueCountFrequency (%) 
53279817.1%
 
43898720.3%
 
35227027.3%
 
2114986.0%
 
133351.7%
 

PLZ8_HHZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing52764
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean3.634892863
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:09.487789image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9336602633
Coefficient of variation (CV)0.2568604629
Kurtosis-0.7021040933
Mean3.634892863
Median Absolute Deviation (MAD)1
Skewness0.01656171981
Sum504843
Variance0.8717214873
MonotocityNot monotonic
2020-11-30T23:56:09.570776image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35823230.4%
 
43837820.0%
 
53105316.2%
 
2101455.3%
 
110800.6%
 
(Missing)5276427.5%
 
ValueCountFrequency (%) 
110800.6%
 
2101455.3%
 
35823230.4%
 
43837820.0%
 
53105316.2%
 
ValueCountFrequency (%) 
53105316.2%
 
43837820.0%
 
35823230.4%
 
2101455.3%
 
110800.6%
 

PRAEGENDE_JUGENDJAHRE
Real number (ℝ≥0)

ZEROS

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.248272911
Minimum0
Maximum15
Zeros48487
Zeros (%)25.3%
Memory size1.5 MiB
2020-11-30T23:56:09.664223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q36
95-th percentile11
Maximum15
Range15
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.807670852
Coefficient of variation (CV)0.8962867809
Kurtosis-0.08445305812
Mean4.248272911
Median Absolute Deviation (MAD)3
Skewness0.7543637158
Sum814190
Variance14.49835732
MonotocityNot monotonic
2020-11-30T23:56:09.750227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%) 
04848725.3%
 
42221611.6%
 
32036110.6%
 
5177529.3%
 
6154578.1%
 
8149107.8%
 
2113165.9%
 
9111335.8%
 
1104055.4%
 
1162463.3%
 
1050332.6%
 
1436211.9%
 
1525501.3%
 
78640.5%
 
127140.4%
 
135870.3%
 
ValueCountFrequency (%) 
04848725.3%
 
1104055.4%
 
2113165.9%
 
32036110.6%
 
42221611.6%
 
5177529.3%
 
6154578.1%
 
78640.5%
 
8149107.8%
 
9111335.8%
 
ValueCountFrequency (%) 
1525501.3%
 
1436211.9%
 
135870.3%
 
127140.4%
 
1162463.3%
 
1050332.6%
 
9111335.8%
 
8149107.8%
 
78640.5%
 
6154578.1%
 

REGIOTYP
Real number (ℝ≥0)

MISSING
ZEROS

Distinct8
Distinct (%)< 0.1%
Missing54260
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean3.814341446
Minimum0
Maximum7
Zeros5804
Zeros (%)3.0%
Memory size1.5 MiB
2020-11-30T23:56:09.838750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.075154504
Coefficient of variation (CV)0.5440400481
Kurtosis-1.252133111
Mean3.814341446
Median Absolute Deviation (MAD)2
Skewness-0.1150760449
Sum524060
Variance4.306266216
MonotocityNot monotonic
2020-11-30T23:56:09.917784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
62850614.9%
 
22186611.4%
 
52141511.2%
 
31976410.3%
 
1173629.1%
 
7116216.1%
 
4110545.8%
 
058043.0%
 
(Missing)5426028.3%
 
ValueCountFrequency (%) 
058043.0%
 
1173629.1%
 
22186611.4%
 
31976410.3%
 
4110545.8%
 
52141511.2%
 
62850614.9%
 
7116216.1%
 
ValueCountFrequency (%) 
7116216.1%
 
62850614.9%
 
52141511.2%
 
4110545.8%
 
31976410.3%
 
22186611.4%
 
1173629.1%
 
058043.0%
 

RELAT_AB
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing50476
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean2.898509662
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:10.001765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.422682617
Coefficient of variation (CV)0.4908324564
Kurtosis-1.152442233
Mean2.898509662
Median Absolute Deviation (MAD)1
Skewness0.127945574
Sum409200
Variance2.024025829
MonotocityNot monotonic
2020-11-30T23:56:10.083576image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
34201221.9%
 
13334117.4%
 
52906815.2%
 
22132611.1%
 
4154068.0%
 
923< 0.1%
 
(Missing)5047626.3%
 
ValueCountFrequency (%) 
13334117.4%
 
22132611.1%
 
34201221.9%
 
4154068.0%
 
52906815.2%
 
923< 0.1%
 
ValueCountFrequency (%) 
923< 0.1%
 
52906815.2%
 
4154068.0%
 
34201221.9%
 
22132611.1%
 
13334117.4%
 

RETOURTYP_BK_S
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean3.716311379
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:10.170966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.113932757
Coefficient of variation (CV)0.2997415026
Kurtosis-1.053611203
Mean3.716311379
Median Absolute Deviation (MAD)1
Skewness-0.1369321587
Sum700298
Variance1.240846187
MonotocityNot monotonic
2020-11-30T23:56:10.255837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
38329743.5%
 
57098537.0%
 
4156538.2%
 
2143667.5%
 
141382.2%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
141382.2%
 
2143667.5%
 
38329743.5%
 
4156538.2%
 
57098537.0%
 
ValueCountFrequency (%) 
57098537.0%
 
4156538.2%
 
38329743.5%
 
2143667.5%
 
141382.2%
 

RT_KEIN_ANREIZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean2.462483881
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:10.348842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.315405169
Coefficient of variation (CV)0.5341781844
Kurtosis-1.517156495
Mean2.462483881
Median Absolute Deviation (MAD)1
Skewness0.1953692323
Sum464028
Variance1.730290758
MonotocityNot monotonic
2020-11-30T23:56:10.434268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
16653334.7%
 
45845230.5%
 
23642119.0%
 
32216011.6%
 
548732.5%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
16653334.7%
 
23642119.0%
 
32216011.6%
 
45845230.5%
 
548732.5%
 
ValueCountFrequency (%) 
548732.5%
 
45845230.5%
 
32216011.6%
 
23642119.0%
 
16653334.7%
 

RT_SCHNAEPPCHEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing3213
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean4.528515859
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:10.523574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.939708373
Coefficient of variation (CV)0.2075091271
Kurtosis3.558854859
Mean4.528515859
Median Absolute Deviation (MAD)0
Skewness-2.086652629
Sum853349
Variance0.8830518262
MonotocityNot monotonic
2020-11-30T23:56:10.607310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
514028173.2%
 
42316812.1%
 
3126286.6%
 
290264.7%
 
133361.7%
 
(Missing)32131.7%
 
ValueCountFrequency (%) 
133361.7%
 
290264.7%
 
3126286.6%
 
42316812.1%
 
514028173.2%
 
ValueCountFrequency (%) 
514028173.2%
 
42316812.1%
 
3126286.6%
 
290264.7%
 
133361.7%
 

RT_UEBERGROESSE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing44192
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean2.519652787
Minimum0
Maximum5
Zeros1903
Zeros (%)1.0%
Memory size1.5 MiB
2020-11-30T23:56:10.695386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.356234719
Coefficient of variation (CV)0.538262544
Kurtosis-0.7664115865
Mean2.519652787
Median Absolute Deviation (MAD)1
Skewness0.5205391682
Sum371548
Variance1.839372614
MonotocityNot monotonic
2020-11-30T23:56:10.775334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
24551023.7%
 
13691319.3%
 
32929815.3%
 
52037710.6%
 
4134597.0%
 
019031.0%
 
(Missing)4419223.1%
 
ValueCountFrequency (%) 
019031.0%
 
13691319.3%
 
24551023.7%
 
32929815.3%
 
4134597.0%
 
52037710.6%
 
ValueCountFrequency (%) 
52037710.6%
 
4134597.0%
 
32929815.3%
 
24551023.7%
 
13691319.3%
 
019031.0%
 

SEMIO_DOM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.483835285
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:10.855268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.631940929
Coefficient of variation (CV)0.3639609453
Kurtosis-0.9623202524
Mean4.483835285
Median Absolute Deviation (MAD)1
Skewness-0.3881830332
Sum859336
Variance2.663231195
MonotocityNot monotonic
2020-11-30T23:56:10.934902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
65778830.2%
 
35021326.2%
 
54194921.9%
 
7117506.1%
 
2116456.1%
 
494594.9%
 
188484.6%
 
ValueCountFrequency (%) 
188484.6%
 
2116456.1%
 
35021326.2%
 
494594.9%
 
54194921.9%
 
65778830.2%
 
7117506.1%
 
ValueCountFrequency (%) 
7117506.1%
 
65778830.2%
 
54194921.9%
 
494594.9%
 
35021326.2%
 
2116456.1%
 
188484.6%
 

SEMIO_ERL
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.408020788
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:11.016591image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.72090874
Coefficient of variation (CV)0.390403953
Kurtosis-1.294525267
Mean4.408020788
Median Absolute Deviation (MAD)1
Skewness0.5593272693
Sum844806
Variance2.961526892
MonotocityNot monotonic
2020-11-30T23:56:11.089460image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
38641545.1%
 
74736524.7%
 
43648019.0%
 
6151487.9%
 
226981.4%
 
520641.1%
 
114820.8%
 
ValueCountFrequency (%) 
114820.8%
 
226981.4%
 
38641545.1%
 
43648019.0%
 
520641.1%
 
6151487.9%
 
74736524.7%
 
ValueCountFrequency (%) 
74736524.7%
 
6151487.9%
 
520641.1%
 
43648019.0%
 
38641545.1%
 
226981.4%
 
114820.8%
 

SEMIO_FAM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.414026465
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:11.173227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q36
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.733128068
Coefficient of variation (CV)0.3926410686
Kurtosis-0.9264928065
Mean4.414026465
Median Absolute Deviation (MAD)1
Skewness-0.5926898725
Sum845957
Variance3.0037329
MonotocityNot monotonic
2020-11-30T23:56:11.254013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
67320938.2%
 
43110016.2%
 
52674514.0%
 
22255411.8%
 
3179599.4%
 
1151677.9%
 
749182.6%
 
ValueCountFrequency (%) 
1151677.9%
 
22255411.8%
 
3179599.4%
 
43110016.2%
 
52674514.0%
 
67320938.2%
 
749182.6%
 
ValueCountFrequency (%) 
749182.6%
 
67320938.2%
 
52674514.0%
 
43110016.2%
 
3179599.4%
 
22255411.8%
 
1151677.9%
 

SEMIO_KAEM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.187245633
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:11.337963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.872047112
Coefficient of variation (CV)0.4470831846
Kurtosis-1.363369895
Mean4.187245633
Median Absolute Deviation (MAD)2
Skewness-0.1802487997
Sum802494
Variance3.50456039
MonotocityNot monotonic
2020-11-30T23:56:11.416138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
66652834.7%
 
35272527.5%
 
22004210.5%
 
1180259.4%
 
5160008.3%
 
7112385.9%
 
470943.7%
 
ValueCountFrequency (%) 
1180259.4%
 
22004210.5%
 
35272527.5%
 
470943.7%
 
5160008.3%
 
66652834.7%
 
7112385.9%
 
ValueCountFrequency (%) 
7112385.9%
 
66652834.7%
 
5160008.3%
 
470943.7%
 
35272527.5%
 
22004210.5%
 
1180259.4%
 

SEMIO_KRIT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.674535095
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:11.499197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.041058635
Coefficient of variation (CV)0.4366335033
Kurtosis-1.297746471
Mean4.674535095
Median Absolute Deviation (MAD)2
Skewness-0.2053341751
Sum895884
Variance4.16592035
MonotocityNot monotonic
2020-11-30T23:56:11.575226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
76419033.5%
 
36017931.4%
 
51950010.2%
 
1174759.1%
 
6163208.5%
 
4125736.6%
 
214150.7%
 
ValueCountFrequency (%) 
1174759.1%
 
214150.7%
 
36017931.4%
 
4125736.6%
 
51950010.2%
 
6163208.5%
 
76419033.5%
 
ValueCountFrequency (%) 
76419033.5%
 
6163208.5%
 
51950010.2%
 
4125736.6%
 
36017931.4%
 
214150.7%
 
1174759.1%
 

SEMIO_KULT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.682497443
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:11.658635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.573090127
Coefficient of variation (CV)0.4271802361
Kurtosis-0.6129899191
Mean3.682497443
Median Absolute Deviation (MAD)1
Skewness-0.00719480503
Sum705758
Variance2.474612548
MonotocityNot monotonic
2020-11-30T23:56:11.735543image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
35741030.0%
 
44391922.9%
 
52587513.5%
 
12573213.4%
 
62536713.2%
 
285804.5%
 
747692.5%
 
ValueCountFrequency (%) 
12573213.4%
 
285804.5%
 
35741030.0%
 
44391922.9%
 
52587513.5%
 
62536713.2%
 
747692.5%
 
ValueCountFrequency (%) 
747692.5%
 
62536713.2%
 
52587513.5%
 
44391922.9%
 
35741030.0%
 
285804.5%
 
12573213.4%
 

SEMIO_LUST
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.366476739
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:11.817958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median5
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.443103117
Coefficient of variation (CV)0.2689107188
Kurtosis1.079596428
Mean5.366476739
Median Absolute Deviation (MAD)1
Skewness-0.9070567185
Sum1028496
Variance2.082546607
MonotocityNot monotonic
2020-11-30T23:56:11.895472image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
57459838.9%
 
75768130.1%
 
42435912.7%
 
62195211.5%
 
163023.3%
 
239912.1%
 
327691.4%
 
ValueCountFrequency (%) 
163023.3%
 
239912.1%
 
327691.4%
 
42435912.7%
 
57459838.9%
 
62195211.5%
 
75768130.1%
 
ValueCountFrequency (%) 
75768130.1%
 
62195211.5%
 
57459838.9%
 
42435912.7%
 
327691.4%
 
239912.1%
 
163023.3%
 

SEMIO_MAT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.883163233
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:11.978865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.840130675
Coefficient of variation (CV)0.4738741497
Kurtosis-1.219700634
Mean3.883163233
Median Absolute Deviation (MAD)2
Skewness-0.3838452685
Sum744216
Variance3.386080903
MonotocityNot monotonic
2020-11-30T23:56:12.057458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
55365828.0%
 
63705419.3%
 
13572218.6%
 
42701514.1%
 
21991310.4%
 
3145097.6%
 
737812.0%
 
ValueCountFrequency (%) 
13572218.6%
 
21991310.4%
 
3145097.6%
 
42701514.1%
 
55365828.0%
 
63705419.3%
 
737812.0%
 
ValueCountFrequency (%) 
737812.0%
 
63705419.3%
 
55365828.0%
 
42701514.1%
 
3145097.6%
 
21991310.4%
 
13572218.6%
 

SEMIO_PFLICHT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.528254336
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:12.138684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.493916302
Coefficient of variation (CV)0.4234151395
Kurtosis-0.8635096163
Mean3.528254336
Median Absolute Deviation (MAD)1
Skewness-0.1434945519
Sum676197
Variance2.231785917
MonotocityNot monotonic
2020-11-30T23:56:12.215015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
55720929.9%
 
44009420.9%
 
23324517.3%
 
33172016.6%
 
12239411.7%
 
737922.0%
 
631981.7%
 
ValueCountFrequency (%) 
12239411.7%
 
23324517.3%
 
33172016.6%
 
44009420.9%
 
55720929.9%
 
631981.7%
 
737922.0%
 
ValueCountFrequency (%) 
737922.0%
 
631981.7%
 
55720929.9%
 
44009420.9%
 
33172016.6%
 
23324517.3%
 
12239411.7%
 

SEMIO_RAT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.16587878
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:12.297083image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.31622125
Coefficient of variation (CV)0.4157522575
Kurtosis-0.2915751031
Mean3.16587878
Median Absolute Deviation (MAD)1
Skewness-0.006427141384
Sum606747
Variance1.732438379
MonotocityNot monotonic
2020-11-30T23:56:12.375161image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
46715535.0%
 
34466823.3%
 
22983315.6%
 
12817114.7%
 
5169248.8%
 
626411.4%
 
722601.2%
 
ValueCountFrequency (%) 
12817114.7%
 
22983315.6%
 
34466823.3%
 
46715535.0%
 
5169248.8%
 
626411.4%
 
722601.2%
 
ValueCountFrequency (%) 
722601.2%
 
626411.4%
 
5169248.8%
 
46715535.0%
 
34466823.3%
 
22983315.6%
 
12817114.7%
 

SEMIO_REL
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.112787761
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:12.459316image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.070958407
Coefficient of variation (CV)0.5035412784
Kurtosis-1.248722527
Mean4.112787761
Median Absolute Deviation (MAD)2
Skewness0.1823009609
Sum788224
Variance4.288868724
MonotocityNot monotonic
2020-11-30T23:56:12.536240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
75101226.6%
 
43820919.9%
 
33256717.0%
 
22959315.4%
 
12069510.8%
 
5167348.7%
 
628421.5%
 
ValueCountFrequency (%) 
12069510.8%
 
22959315.4%
 
33256717.0%
 
43820919.9%
 
5167348.7%
 
628421.5%
 
75101226.6%
 
ValueCountFrequency (%) 
75101226.6%
 
628421.5%
 
5167348.7%
 
43820919.9%
 
33256717.0%
 
22959315.4%
 
12069510.8%
 

SEMIO_SOZ
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.74213679
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:12.616862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q36
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.718039291
Coefficient of variation (CV)0.4591064912
Kurtosis-1.375940563
Mean3.74213679
Median Absolute Deviation (MAD)1
Skewness0.2940602431
Sum717188
Variance2.951659006
MonotocityNot monotonic
2020-11-30T23:56:12.693067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
26230232.5%
 
64783525.0%
 
33154216.5%
 
42623113.7%
 
5134177.0%
 
155562.9%
 
747692.5%
 
ValueCountFrequency (%) 
155562.9%
 
26230232.5%
 
33154216.5%
 
42623113.7%
 
5134177.0%
 
64783525.0%
 
747692.5%
 
ValueCountFrequency (%) 
747692.5%
 
64783525.0%
 
5134177.0%
 
42623113.7%
 
33154216.5%
 
26230232.5%
 
155562.9%
 

SEMIO_TRADV
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.919160771
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:12.775260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.219223944
Coefficient of variation (CV)0.4176624857
Kurtosis0.268519283
Mean2.919160771
Median Absolute Deviation (MAD)1
Skewness0.1016729042
Sum559463
Variance1.486507025
MonotocityNot monotonic
2020-11-30T23:56:12.853418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
37011536.6%
 
45494528.7%
 
13525718.4%
 
22280611.9%
 
547692.5%
 
720641.1%
 
616960.9%
 
ValueCountFrequency (%) 
13525718.4%
 
22280611.9%
 
37011536.6%
 
45494528.7%
 
547692.5%
 
616960.9%
 
720641.1%
 
ValueCountFrequency (%) 
720641.1%
 
616960.9%
 
547692.5%
 
45494528.7%
 
37011536.6%
 
22280611.9%
 
13525718.4%
 

SEMIO_VERT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.185278526
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:12.939178image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.367406672
Coefficient of variation (CV)0.5656509256
Kurtosis-1.539957163
Mean4.185278526
Median Absolute Deviation (MAD)2
Skewness-0.2238432493
Sum802117
Variance5.60461435
MonotocityNot monotonic
2020-11-30T23:56:13.013534image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
15037926.3%
 
74654924.3%
 
62919215.2%
 
52515413.1%
 
4187879.8%
 
2149487.8%
 
366433.5%
 
ValueCountFrequency (%) 
15037926.3%
 
2149487.8%
 
366433.5%
 
4187879.8%
 
52515413.1%
 
62919215.2%
 
74654924.3%
 
ValueCountFrequency (%) 
74654924.3%
 
62919215.2%
 
52515413.1%
 
4187879.8%
 
366433.5%
 
2149487.8%
 
15037926.3%
 

SHOPPER_TYP
Real number (ℝ)

ZEROS

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9877538455
Minimum-1
Maximum3
Zeros30054
Zeros (%)15.7%
Memory size1.5 MiB
2020-11-30T23:56:13.097270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median1
Q33
95-th percentile3
Maximum3
Range4
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.538679303
Coefficient of variation (CV)1.557755822
Kurtosis-1.459428076
Mean0.9877538455
Median Absolute Deviation (MAD)2
Skewness0.03808198834
Sum189305
Variance2.367533998
MonotocityNot monotonic
2020-11-30T23:56:13.177684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
35103426.6%
 
-14899025.6%
 
13795519.8%
 
03005415.7%
 
22361912.3%
 
ValueCountFrequency (%) 
-14899025.6%
 
03005415.7%
 
13795519.8%
 
22361912.3%
 
35103426.6%
 
ValueCountFrequency (%) 
35103426.6%
 
22361912.3%
 
13795519.8%
 
03005415.7%
 
-14899025.6%
 

SOHO_KZ
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Memory size1.5 MiB
0
143625 
1
 
1431
(Missing)
46596 
ValueCountFrequency (%) 
014362574.9%
 
114310.7%
 
(Missing)4659624.3%
 

STRUKTURTYP
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing50476
Missing (%)26.3%
Memory size1.5 MiB
3
99912 
2
21506 
1
19758 
ValueCountFrequency (%) 
39991252.1%
 
22150611.2%
 
11975810.3%
 
(Missing)5047626.3%
 
2020-11-30T23:56:13.286442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.14117624.6%
 
014117624.6%
 
n10095217.6%
 
39991217.4%
 
a504768.8%
 
2215063.7%
 
1197583.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number28235249.1%
 
Lowercase Letter15142826.3%
 
Other Punctuation14117624.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
014117650.0%
 
39991235.4%
 
2215067.6%
 
1197587.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.141176100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n10095266.7%
 
a5047633.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42352873.7%
 
Latin15142826.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
.14117633.3%
 
014117633.3%
 
39991223.6%
 
2215065.1%
 
1197584.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n10095266.7%
 
a5047633.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII574956100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.14117624.6%
 
014117624.6%
 
n10095217.6%
 
39991217.4%
 
a504768.8%
 
2215063.7%
 
1197583.4%
 

TITEL_KZ
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean0.02168128171
Minimum0
Maximum5
Zeros142744
Zeros (%)74.5%
Memory size1.5 MiB
2020-11-30T23:56:13.376232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2104244816
Coefficient of variation (CV)9.705352495
Kurtosis271.7479422
Mean0.02168128171
Median Absolute Deviation (MAD)0
Skewness14.77601324
Sum3145
Variance0.04427846244
MonotocityNot monotonic
2020-11-30T23:56:13.460302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
014274474.5%
 
120171.1%
 
41250.1%
 
31110.1%
 
559< 0.1%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
014274474.5%
 
120171.1%
 
31110.1%
 
41250.1%
 
559< 0.1%
 
ValueCountFrequency (%) 
559< 0.1%
 
41250.1%
 
31110.1%
 
120171.1%
 
014274474.5%
 

UMFELD_ALT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing50448
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean2.968010821
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:13.544047image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.312128377
Coefficient of variation (CV)0.4420901593
Kurtosis-1.09648851
Mean2.968010821
Median Absolute Deviation (MAD)1
Skewness-0.0264404704
Sum419095
Variance1.721680877
MonotocityNot monotonic
2020-11-30T23:56:13.628300image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
33696119.3%
 
43123716.3%
 
22667013.9%
 
12543913.3%
 
52089710.9%
 
(Missing)5044826.3%
 
ValueCountFrequency (%) 
12543913.3%
 
22667013.9%
 
33696119.3%
 
43123716.3%
 
52089710.9%
 
ValueCountFrequency (%) 
52089710.9%
 
43123716.3%
 
33696119.3%
 
22667013.9%
 
12543913.3%
 

UMFELD_JUNG
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing50448
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean4.335769525
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:13.719664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9797005376
Coefficient of variation (CV)0.2259577065
Kurtosis1.979689818
Mean4.335769525
Median Absolute Deviation (MAD)0
Skewness-1.574479964
Sum612228
Variance0.9598131434
MonotocityNot monotonic
2020-11-30T23:56:13.805433image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
58365543.6%
 
43375617.6%
 
3146687.7%
 
258003.0%
 
133251.7%
 
(Missing)5044826.3%
 
ValueCountFrequency (%) 
133251.7%
 
258003.0%
 
3146687.7%
 
43375617.6%
 
58365543.6%
 
ValueCountFrequency (%) 
58365543.6%
 
43375617.6%
 
3146687.7%
 
258003.0%
 
133251.7%
 

UNGLEICHENN_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Memory size1.5 MiB
0
132763 
1
 
12293
(Missing)
46596 
ValueCountFrequency (%) 
013276369.3%
 
1122936.4%
 
(Missing)4659624.3%
 

VERDICHTUNGSRAUM
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)< 0.1%
Missing50476
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean5.055087267
Minimum0
Maximum45
Zeros65984
Zeros (%)34.4%
Memory size1.5 MiB
2020-11-30T23:56:13.924457image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile28
Maximum45
Range45
Interquartile range (IQR)6

Descriptive statistics

Standard deviation9.250234572
Coefficient of variation (CV)1.829886228
Kurtosis4.88311212
Mean5.055087267
Median Absolute Deviation (MAD)1
Skewness2.329566347
Sum713657
Variance85.56683964
MonotocityNot monotonic
2020-11-30T23:56:14.036256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%) 
06598434.4%
 
12085710.9%
 
367993.5%
 
664493.4%
 
451842.7%
 
237321.9%
 
732981.7%
 
827661.4%
 
520631.1%
 
2417600.9%
 
1216270.8%
 
1715450.8%
 
1812830.7%
 
1111550.6%
 
1611420.6%
 
3310670.6%
 
2510600.6%
 
279940.5%
 
139070.5%
 
238910.5%
 
108310.4%
 
97680.4%
 
327600.4%
 
297070.4%
 
147010.4%
 
Other values (21)68463.6%
 
(Missing)5047626.3%
 
ValueCountFrequency (%) 
06598434.4%
 
12085710.9%
 
237321.9%
 
367993.5%
 
451842.7%
 
520631.1%
 
664493.4%
 
732981.7%
 
827661.4%
 
97680.4%
 
ValueCountFrequency (%) 
453780.2%
 
444640.2%
 
431450.1%
 
424480.2%
 
4171< 0.1%
 
4059< 0.1%
 
391960.1%
 
385920.3%
 
3764< 0.1%
 
366380.3%
 

VERS_TYP
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
1
73620 
2
69042 
-1
48990 
ValueCountFrequency (%) 
17362038.4%
 
26904236.0%
 
-14899025.6%
 
2020-11-30T23:56:14.144478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
112261051.0%
 
26904228.7%
 
-4899020.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number19165279.6%
 
Dash Punctuation4899020.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
112261064.0%
 
26904236.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-48990100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common240642100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
112261051.0%
 
26904228.7%
 
-4899020.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII240642100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
112261051.0%
 
26904228.7%
 
-4899020.4%
 

VHA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean0.8685335319
Minimum0
Maximum5
Zeros74250
Zeros (%)38.7%
Memory size1.5 MiB
2020-11-30T23:56:14.224156image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.320530263
Coefficient of variation (CV)1.52041368
Kurtosis3.115032695
Mean0.8685335319
Median Absolute Deviation (MAD)0
Skewness1.971956014
Sum125986
Variance1.743800175
MonotocityNot monotonic
2020-11-30T23:56:14.308465image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
07425038.7%
 
15237627.3%
 
570013.7%
 
452592.7%
 
352292.7%
 
29410.5%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
07425038.7%
 
15237627.3%
 
29410.5%
 
352292.7%
 
452592.7%
 
570013.7%
 
ValueCountFrequency (%) 
570013.7%
 
452592.7%
 
352292.7%
 
29410.5%
 
15237627.3%
 
07425038.7%
 

VHN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing54260
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean2.429508268
Minimum0
Maximum4
Zeros5804
Zeros (%)3.0%
Memory size1.5 MiB
2020-11-30T23:56:14.394057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.148821197
Coefficient of variation (CV)0.4728616125
Kurtosis-0.896137573
Mean2.429508268
Median Absolute Deviation (MAD)1
Skewness-0.138773734
Sum333795
Variance1.319790143
MonotocityNot monotonic
2020-11-30T23:56:14.474959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
24384922.9%
 
43190616.6%
 
33132016.3%
 
12451312.8%
 
058043.0%
 
(Missing)5426028.3%
 
ValueCountFrequency (%) 
058043.0%
 
12451312.8%
 
24384922.9%
 
33132016.3%
 
43190616.6%
 
ValueCountFrequency (%) 
43190616.6%
 
33132016.3%
 
24384922.9%
 
12451312.8%
 
058043.0%
 

VK_DHT4A
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)< 0.1%
Missing47871
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean4.374416648
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:14.564142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile10
Maximum11
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.924355416
Coefficient of variation (CV)0.6685132331
Kurtosis-1.094468891
Mean4.374416648
Median Absolute Deviation (MAD)3
Skewness0.4529847245
Sum628958
Variance8.551854599
MonotocityNot monotonic
2020-11-30T23:56:14.647248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
13174716.6%
 
22112011.0%
 
3167688.7%
 
7142827.5%
 
4115096.0%
 
6113655.9%
 
5106855.6%
 
1088654.6%
 
988424.6%
 
885884.5%
 
1110< 0.1%
 
(Missing)4787125.0%
 
ValueCountFrequency (%) 
13174716.6%
 
22112011.0%
 
3167688.7%
 
4115096.0%
 
5106855.6%
 
6113655.9%
 
7142827.5%
 
885884.5%
 
988424.6%
 
1088654.6%
 
ValueCountFrequency (%) 
1110< 0.1%
 
1088654.6%
 
988424.6%
 
885884.5%
 
7142827.5%
 
6113655.9%
 
5106855.6%
 
4115096.0%
 
3167688.7%
 
22112011.0%
 

VK_DISTANZ
Real number (ℝ≥0)

MISSING

Distinct13
Distinct (%)< 0.1%
Missing47871
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean4.564768641
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:14.727485image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile10
Maximum13
Range12
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.887034938
Coefficient of variation (CV)0.6324602986
Kurtosis-0.432615138
Mean4.564768641
Median Absolute Deviation (MAD)2
Skewness0.5634636033
Sum656327
Variance8.334970733
MonotocityNot monotonic
2020-11-30T23:56:14.814994image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
12773614.5%
 
32237811.7%
 
62076910.8%
 
4152628.0%
 
2131726.9%
 
7126126.6%
 
892724.8%
 
582234.3%
 
959053.1%
 
1034061.8%
 
1126031.4%
 
1217210.9%
 
137220.4%
 
(Missing)4787125.0%
 
ValueCountFrequency (%) 
12773614.5%
 
2131726.9%
 
32237811.7%
 
4152628.0%
 
582234.3%
 
62076910.8%
 
7126126.6%
 
892724.8%
 
959053.1%
 
1034061.8%
 
ValueCountFrequency (%) 
137220.4%
 
1217210.9%
 
1126031.4%
 
1034061.8%
 
959053.1%
 
892724.8%
 
7126126.6%
 
62076910.8%
 
582234.3%
 
4152628.0%
 

VK_ZG11
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)< 0.1%
Missing47871
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean3.168867931
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:14.899002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile8
Maximum11
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.233515815
Coefficient of variation (CV)0.7048308303
Kurtosis1.753072506
Mean3.168867931
Median Absolute Deviation (MAD)1
Skewness1.381714244
Sum455623
Variance4.988592896
MonotocityNot monotonic
2020-11-30T23:56:14.986220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
13684619.2%
 
23319217.3%
 
32541213.3%
 
4170128.9%
 
5122256.4%
 
666253.5%
 
735221.8%
 
831131.6%
 
925821.3%
 
1119181.0%
 
1013340.7%
 
(Missing)4787125.0%
 
ValueCountFrequency (%) 
13684619.2%
 
23319217.3%
 
32541213.3%
 
4170128.9%
 
5122256.4%
 
666253.5%
 
735221.8%
 
831131.6%
 
925821.3%
 
1013340.7%
 
ValueCountFrequency (%) 
1119181.0%
 
1013340.7%
 
925821.3%
 
831131.6%
 
735221.8%
 
666253.5%
 
5122256.4%
 
4170128.9%
 
32541213.3%
 
23319217.3%
 

W_KEIT_KIND_HH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing53742
Missing (%)28.0%
Infinite0
Infinite (%)0.0%
Mean4.152715539
Minimum0
Maximum6
Zeros3195
Zeros (%)1.7%
Memory size1.5 MiB
2020-11-30T23:56:15.068650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median5
Q36
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.974374585
Coefficient of variation (CV)0.4754418082
Kurtosis-1.322027583
Mean4.152715539
Median Absolute Deviation (MAD)1
Skewness-0.4630565154
Sum572701
Variance3.898155001
MonotocityNot monotonic
2020-11-30T23:56:15.147082image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
66384133.3%
 
22559613.4%
 
4145157.6%
 
1126476.6%
 
3114126.0%
 
567043.5%
 
031951.7%
 
(Missing)5374228.0%
 
ValueCountFrequency (%) 
031951.7%
 
1126476.6%
 
22559613.4%
 
3114126.0%
 
4145157.6%
 
567043.5%
 
66384133.3%
 
ValueCountFrequency (%) 
66384133.3%
 
567043.5%
 
4145157.6%
 
3114126.0%
 
22559613.4%
 
1126476.6%
 
031951.7%
 

WOHNDAUER_2008
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing46596
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean8.646371057
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:15.232501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q19
median9
Q39
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.154000554
Coefficient of variation (CV)0.1334664619
Kurtosis13.26062379
Mean8.646371057
Median Absolute Deviation (MAD)0
Skewness-3.689679911
Sum1254208
Variance1.331717278
MonotocityNot monotonic
2020-11-30T23:56:15.315171image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
912726666.4%
 
869243.6%
 
424761.3%
 
623511.2%
 
321151.1%
 
719931.0%
 
517840.9%
 
1980.1%
 
249< 0.1%
 
(Missing)4659624.3%
 
ValueCountFrequency (%) 
1980.1%
 
249< 0.1%
 
321151.1%
 
424761.3%
 
517840.9%
 
623511.2%
 
719931.0%
 
869243.6%
 
912726666.4%
 
ValueCountFrequency (%) 
912726666.4%
 
869243.6%
 
719931.0%
 
623511.2%
 
517840.9%
 
424761.3%
 
321151.1%
 
249< 0.1%
 
1980.1%
 

WOHNLAGE
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing49927
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean3.723132828
Minimum0
Maximum8
Zeros1107
Zeros (%)0.6%
Memory size1.5 MiB
2020-11-30T23:56:15.407193image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q35
95-th percentile7
Maximum8
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.095540209
Coefficient of variation (CV)0.5628432574
Kurtosis-0.9042610323
Mean3.723132828
Median Absolute Deviation (MAD)1
Skewness0.5797956838
Sum527661
Variance4.391288766
MonotocityNot monotonic
2020-11-30T23:56:15.488496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
34507423.5%
 
73132816.3%
 
22442712.7%
 
1165678.6%
 
4150967.9%
 
558903.1%
 
822361.2%
 
011070.6%
 
(Missing)4992726.1%
 
ValueCountFrequency (%) 
011070.6%
 
1165678.6%
 
22442712.7%
 
34507423.5%
 
4150967.9%
 
558903.1%
 
73132816.3%
 
822361.2%
 
ValueCountFrequency (%) 
822361.2%
 
73132816.3%
 
558903.1%
 
4150967.9%
 
34507423.5%
 
22442712.7%
 
1165678.6%
 
011070.6%
 

ZABEOTYP
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.576805877
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:15.571288image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q33
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.168485772
Coefficient of variation (CV)0.4534628635
Kurtosis0.4729641663
Mean2.576805877
Median Absolute Deviation (MAD)0
Skewness0.2822703633
Sum493850
Variance1.365358999
MonotocityNot monotonic
2020-11-30T23:56:15.653397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
310868256.7%
 
15434728.4%
 
4148097.7%
 
268993.6%
 
658483.1%
 
510670.6%
 
ValueCountFrequency (%) 
15434728.4%
 
268993.6%
 
310868256.7%
 
4148097.7%
 
510670.6%
 
658483.1%
 
ValueCountFrequency (%) 
658483.1%
 
510670.6%
 
4148097.7%
 
310868256.7%
 
268993.6%
 
15434728.4%
 

PRODUCT_GROUP
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
COSMETIC_AND_FOOD
100860 
FOOD
47382 
COSMETIC
43410 
ValueCountFrequency (%) 
COSMETIC_AND_FOOD10086052.6%
 
FOOD4738224.7%
 
COSMETIC4341022.7%
 
2020-11-30T23:56:15.748905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters12
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
O44075419.6%
 
C28854012.8%
 
D24910211.1%
 
_2017209.0%
 
F1482426.6%
 
S1442706.4%
 
M1442706.4%
 
E1442706.4%
 
T1442706.4%
 
I1442706.4%
 
A1008604.5%
 
N1008604.5%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter204970891.0%
 
Connector Punctuation2017209.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
O44075421.5%
 
C28854014.1%
 
D24910212.2%
 
F1482427.2%
 
S1442707.0%
 
M1442707.0%
 
E1442707.0%
 
T1442707.0%
 
I1442707.0%
 
A1008604.9%
 
N1008604.9%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_201720100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin204970891.0%
 
Common2017209.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
O44075421.5%
 
C28854014.1%
 
D24910212.2%
 
F1482427.2%
 
S1442707.0%
 
M1442707.0%
 
E1442707.0%
 
T1442707.0%
 
I1442707.0%
 
A1008604.9%
 
N1008604.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
_201720100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2251428100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
O44075419.6%
 
C28854012.8%
 
D24910211.1%
 
_2017209.0%
 
F1482426.6%
 
S1442706.4%
 
M1442706.4%
 
E1442706.4%
 
T1442706.4%
 
I1442706.4%
 
A1008604.5%
 
N1008604.5%
 

CUSTOMER_GROUP
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
MULTI_BUYER
132238 
SINGLE_BUYER
59414 
ValueCountFrequency (%) 
MULTI_BUYER13223869.0%
 
SINGLE_BUYER5941431.0%
 
2020-11-30T23:56:15.848151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters13
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
U32389014.9%
 
E25106611.6%
 
L1916528.8%
 
I1916528.8%
 
_1916528.8%
 
B1916528.8%
 
Y1916528.8%
 
R1916528.8%
 
M1322386.1%
 
T1322386.1%
 
S594142.7%
 
N594142.7%
 
G594142.7%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter197593491.2%
 
Connector Punctuation1916528.8%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
U32389016.4%
 
E25106612.7%
 
L1916529.7%
 
I1916529.7%
 
B1916529.7%
 
Y1916529.7%
 
R1916529.7%
 
M1322386.7%
 
T1322386.7%
 
S594143.0%
 
N594143.0%
 
G594143.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_191652100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin197593491.2%
 
Common1916528.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
U32389016.4%
 
E25106612.7%
 
L1916529.7%
 
I1916529.7%
 
B1916529.7%
 
Y1916529.7%
 
R1916529.7%
 
M1322386.7%
 
T1322386.7%
 
S594143.0%
 
N594143.0%
 
G594143.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
_191652100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2167586100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
U32389014.9%
 
E25106611.6%
 
L1916528.8%
 
I1916528.8%
 
_1916528.8%
 
B1916528.8%
 
Y1916528.8%
 
R1916528.8%
 
M1322386.1%
 
T1322386.1%
 
S594142.7%
 
N594142.7%
 
G594142.7%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
0
174356 
1
 
17296
ValueCountFrequency (%) 
017435691.0%
 
1172969.0%
 

ANREDE_KZ
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
1
119508 
2
72144 
ValueCountFrequency (%) 
111950862.4%
 
27214437.6%
 
2020-11-30T23:56:15.947373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters2
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
111950862.4%
 
27214437.6%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number191652100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
111950862.4%
 
27214437.6%
 

Most occurring scripts

ValueCountFrequency (%) 
Common191652100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
111950862.4%
 
27214437.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII191652100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
111950862.4%
 
27214437.6%
 

ALTERSKATEGORIE_GROB
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.060907269
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size1.5 MiB
2020-11-30T23:56:16.026408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.08625367
Coefficient of variation (CV)0.3548796401
Kurtosis0.3778795139
Mean3.060907269
Median Absolute Deviation (MAD)1
Skewness-0.6090711038
Sum586629
Variance1.179947036
MonotocityNot monotonic
2020-11-30T23:56:16.107265image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
48583444.8%
 
35836430.5%
 
12838714.8%
 
2188279.8%
 
92400.1%
 
ValueCountFrequency (%) 
12838714.8%
 
2188279.8%
 
35836430.5%
 
48583444.8%
 
92400.1%
 
ValueCountFrequency (%) 
92400.1%
 
48583444.8%
 
35836430.5%
 
2188279.8%
 
12838714.8%